Meeting Title: Data Engineer Interview (Manam Sai Subhash) Date: 2025-08-06 Meeting participants: Awaish Kumar, sai subhash manam
WEBVTT
1 00:00:55.140 ⇒ 00:00:56.290 sai subhash manam: Hey! I wish.
2 00:01:03.260 ⇒ 00:01:04.330 Awaish Kumar: Hello!
3 00:01:08.160 ⇒ 00:01:08.810 Awaish Kumar: Hello!
4 00:01:08.810 ⇒ 00:01:11.370 sai subhash manam: Like, yeah, I can hear you. Now. Yeah.
5 00:01:14.650 ⇒ 00:01:20.769 Awaish Kumar: Okay? Yeah. So what’s your like? 1st name?
6 00:01:22.030 ⇒ 00:01:24.419 sai subhash manam: My name is Sai. You can call me Sai.
7 00:01:26.040 ⇒ 00:01:26.645 Awaish Kumar: Side.
8 00:01:27.750 ⇒ 00:01:28.470 sai subhash manam: Yeah.
9 00:01:29.050 ⇒ 00:01:30.074 Awaish Kumar: Okay?
10 00:01:31.220 ⇒ 00:01:39.660 Awaish Kumar: so yeah, like, in this interview call, we are going to deep dive into more technical discussions and the projects you have worked on so far.
11 00:01:40.232 ⇒ 00:01:46.509 Awaish Kumar: Hi, my name is Avish Kumar, and I’m engineering manager at the Brain Force. And what
12 00:01:47.160 ⇒ 00:01:48.193 Awaish Kumar: are like,
13 00:01:48.870 ⇒ 00:01:56.539 Awaish Kumar: yeah, like, I will give a little bit introduction of brain food, for example. And then we can start with your introduction.
14 00:01:57.401 ⇒ 00:02:07.618 Awaish Kumar: So Greenforge is a consulting company. We provide data and AI services to grants across different
15 00:02:08.846 ⇒ 00:02:15.800 Awaish Kumar: industries, and mostly of our clients from right now are based in the Us. Especially the Eastern time zone
16 00:02:16.416 ⇒ 00:02:24.699 Awaish Kumar: and like, yeah, but we are continue to get more clients, and we are targeting everybody, at least like around the globe.
17 00:02:25.369 ⇒ 00:02:39.740 Awaish Kumar: Yeah, that’s that’s my main lead, and in terms of like employees, we have places all across the globe working full time and part time with us. And
18 00:02:40.610 ⇒ 00:02:44.890 Awaish Kumar: we are operating remotely like, yeah, that’s that’s the main
19 00:02:47.060 ⇒ 00:02:50.130 Awaish Kumar: that’s mainly how how grateful is operating.
20 00:02:51.130 ⇒ 00:02:57.870 Awaish Kumar: Yeah. Now we can start with your introduction, and we can then take it further from there.
21 00:02:58.990 ⇒ 00:02:59.930 sai subhash manam: Sure thing.
22 00:03:00.100 ⇒ 00:03:03.370 sai subhash manam: So my name is Sai Subashmanam. You can call me Sai.
23 00:03:03.670 ⇒ 00:03:07.979 sai subhash manam: and we are firstly, thank you. This opportunity.
24 00:03:07.980 ⇒ 00:03:08.410 Awaish Kumar: Connecting.
25 00:03:08.410 ⇒ 00:03:08.715 sai subhash manam: So
26 00:03:09.020 ⇒ 00:03:09.700 Awaish Kumar: Tomorrow.
27 00:03:11.320 ⇒ 00:03:15.429 sai subhash manam: Yeah. So I have a Master’s degree in data, science analytics from George’s
28 00:03:15.580 ⇒ 00:03:22.969 sai subhash manam: testing and a Bachelor’s degree in computer science. So during my Master’s degree. I worked as a graduate assistant.
29 00:03:23.290 ⇒ 00:03:32.059 sai subhash manam: and after my graduated working as a temporary paraprofessional at trends, which is a company.
30 00:03:32.800 ⇒ 00:03:36.150 sai subhash manam: and outside my work, I just like to go for a walk.
31 00:03:38.790 ⇒ 00:03:41.859 Awaish Kumar: Your voice is cutting a bit. I don’t know.
32 00:03:43.353 ⇒ 00:03:48.580 Awaish Kumar: Is, is it in? Is there? Is there an Internet problem on this side?
33 00:03:49.590 ⇒ 00:03:52.590 sai subhash manam: Oh, I don’t think so. I can hear you perfectly all right.
34 00:03:52.590 ⇒ 00:03:59.559 Awaish Kumar: Yeah, but your voice is cutting sometimes, and like when you speak longer, it might just cut.
35 00:04:00.613 ⇒ 00:04:01.316 Awaish Kumar: Oh.
36 00:04:02.020 ⇒ 00:04:03.020 sai subhash manam: Is it better now.
37 00:04:05.210 ⇒ 00:04:20.570 Awaish Kumar: Yeah, I can hear you. I’m I’m just saying that when you speak like full sentences, then few words are just cutting down. So if if we are going to get deeper into the technical discussions, and if, like, I don’t hear you what you’re saying, that it will be hard for me to understand.
38 00:04:21.779 ⇒ 00:04:27.639 sai subhash manam: Okay? I can just use connect my earpods for better audio call.
39 00:04:27.869 ⇒ 00:04:28.829 Awaish Kumar: Okay, let’s do it.
40 00:04:38.209 ⇒ 00:04:39.379 sai subhash manam: Is it better now.
41 00:04:42.970 ⇒ 00:04:53.410 Awaish Kumar: I can hear you. Let’s let’s see. Yeah. So you mentioned experiences. Can you please go over that? It was just cutting
42 00:04:53.590 ⇒ 00:04:55.920 Awaish Kumar: what voice was getting. I couldn’t be.
43 00:04:56.500 ⇒ 00:05:03.479 sai subhash manam: Sure thing, I’ll just go again. So basically, my name is Sai Subhash, like I said before you can call me Sai.
44 00:05:03.660 ⇒ 00:05:10.680 sai subhash manam: so I have a Master’s degree in data science from Georgia State University, and a Bachelor’s degree in science as well.
45 00:05:11.240 ⇒ 00:05:18.146 sai subhash manam: So during my Master’s degree, I worked as a graduate research assistant at the data mining lab where I worked on
46 00:05:18.620 ⇒ 00:05:26.119 sai subhash manam: building data pipelines and back end using Django and a front end using react. Js and Chatjs libraries.
47 00:05:26.120 ⇒ 00:05:27.130 Awaish Kumar: Exactly.
48 00:05:27.130 ⇒ 00:05:32.979 sai subhash manam: And my graduation and starting as a technical, paraprofessional
49 00:05:33.150 ⇒ 00:05:46.630 sai subhash manam: and Georgia State University, where I have worked with building docker plans and submitting bad jobs and also working on back end and front end for the web application
50 00:05:48.020 ⇒ 00:05:51.619 sai subhash manam: fun. Fact. Even the application is called Brainforge.
51 00:05:55.620 ⇒ 00:05:55.980 Awaish Kumar: Okay.
52 00:05:56.278 ⇒ 00:05:59.560 sai subhash manam: Application I worked is called is also called a spin pooch.
53 00:06:00.070 ⇒ 00:06:01.910 sai subhash manam: That’s how I got your company.
54 00:06:04.180 ⇒ 00:06:11.620 Awaish Kumar: Okay? And so do you have any professional working experience?
55 00:06:13.250 ⇒ 00:06:14.099 sai subhash manam: Yeah, and I know.
56 00:06:14.500 ⇒ 00:06:20.930 Awaish Kumar: As a full stack developer at Prince Georgia State University itself.
57 00:06:22.780 ⇒ 00:06:26.970 Awaish Kumar: Okay? Like, if I had a lab.
58 00:06:27.250 ⇒ 00:06:31.739 Awaish Kumar: yeah, where? What are your so like, how how
59 00:06:32.050 ⇒ 00:06:36.349 Awaish Kumar: long you have been working as as professional, like software engineer.
60 00:06:37.530 ⇒ 00:06:41.050 sai subhash manam: So I’ve got like a year and a half.
61 00:06:42.780 ⇒ 00:06:47.990 Awaish Kumar: Okay? So you have one and a half years of experience working as a as a full time employee
62 00:06:48.500 ⇒ 00:06:49.520 Awaish Kumar: and.
63 00:06:49.520 ⇒ 00:06:51.719 sai subhash manam: Years of experience, working as a graduate assistant.
64 00:06:53.810 ⇒ 00:07:00.140 Awaish Kumar: Yeah, so, but like it was a bachelor then, master, and then the job. And there’s no
65 00:07:00.838 ⇒ 00:07:05.319 Awaish Kumar: working experience like between bachelors and masters. The total like.
66 00:07:05.320 ⇒ 00:07:10.179 sai subhash manam: No, there’s no no, so I have a after my badge started directly working.
67 00:07:10.370 ⇒ 00:07:11.530 Awaish Kumar: So I just don’t.
68 00:07:11.530 ⇒ 00:07:11.949 sai subhash manam: Today, if you.
69 00:07:11.950 ⇒ 00:07:18.479 Awaish Kumar: And what what you’re looking for like in the in the in the next job.
70 00:07:19.870 ⇒ 00:07:26.269 sai subhash manam: So basically, I just want to work with the latest technologies like what you’re doing at brain foods right now.
71 00:07:27.560 ⇒ 00:07:30.910 Awaish Kumar: Thing is, what are we doing at Brailfort?
72 00:07:31.870 ⇒ 00:07:43.610 sai subhash manam: So at Printforge, I have gone through. So like you build a bunch of versatile tools of a data engine and automation web scraping. And those stuff
73 00:07:43.760 ⇒ 00:07:52.969 sai subhash manam: so. And I know you’re concentrating on any particular industry or tool service. And you can. You can just adapt them to any you work with.
74 00:07:53.490 ⇒ 00:07:56.512 sai subhash manam: So I’m asking for something like that, because,
75 00:07:57.550 ⇒ 00:08:08.769 sai subhash manam: also want to work in a startup environment. Because this this is like the early stages of my career. So I just want to work and learn as much as possible so that I can have good career trajectory.
76 00:08:10.210 ⇒ 00:08:14.509 Awaish Kumar: But your current role is a full stack developer. Right?
77 00:08:14.660 ⇒ 00:08:21.029 Awaish Kumar: Yes, kind of like so and what what role you’re interviewing for is.
78 00:08:22.070 ⇒ 00:08:32.259 sai subhash manam: I’m interviewing for an automation engineer because I’ve gone through the job description. It perfectly aligns with my work doing along so like I’ve been working on it in projects like.
79 00:08:32.419 ⇒ 00:08:39.100 sai subhash manam: I recently worked on an automation tool where I automatically our easy apply jobs in Linkedin
80 00:08:39.429 ⇒ 00:08:44.489 sai subhash manam: See project. I’ve worked on. So now I’ve also constantly with data scraping.
81 00:08:44.960 ⇒ 00:08:53.430 Awaish Kumar: How. But that is like that is that like a very big project, because I don’t interested
82 00:08:53.590 ⇒ 00:08:55.140 Awaish Kumar: something similar.
83 00:08:55.520 ⇒ 00:09:02.609 Awaish Kumar: It’s very simple to build an a writer script which can help you apply automatically on weekend.
84 00:09:02.930 ⇒ 00:09:03.860 Awaish Kumar: So.
85 00:09:04.200 ⇒ 00:09:05.329 sai subhash manam: I don’t want to distract you.
86 00:09:05.330 ⇒ 00:09:10.870 sai subhash manam: Very simple, because Linkedin automatically changes the code pretty frequently.
87 00:09:11.160 ⇒ 00:09:14.509 sai subhash manam: You know what I’m saying. They’ll it’s very difficult to find.
88 00:09:14.510 ⇒ 00:09:19.510 Awaish Kumar: That’s what I’m asking. How? What was it like? How did you handle that? Right?
89 00:09:19.830 ⇒ 00:09:26.909 Awaish Kumar: For example, you are saying you you wrote a written script, or I mean, you worked on a project
90 00:09:27.020 ⇒ 00:09:31.179 Awaish Kumar: which applies the jobs on the Linkedin. And
91 00:09:31.670 ⇒ 00:09:39.372 Awaish Kumar: and then you are saying that Linkedin changes there how to apply like that ui, or whatever
92 00:09:40.400 ⇒ 00:09:48.969 Awaish Kumar: The changes and the the tags, for example, very frequently. So how basically, you solve that problem.
93 00:09:49.420 ⇒ 00:10:07.500 sai subhash manam: So, even though they change the tag names and everything but the core values of like the easy apply button should definitely contain them called easy apply, right? So I targeted the particular keywords in order to figure out what’s going on with the element, and directly find those and
94 00:10:07.620 ⇒ 00:10:08.610 sai subhash manam: do the functionality.
95 00:10:10.600 ⇒ 00:10:13.789 Awaish Kumar: Yeah, I I just wanted to understand your solution like.
96 00:10:14.521 ⇒ 00:10:18.780 Awaish Kumar: This is just one writing one a selector.
97 00:10:19.470 ⇒ 00:10:24.479 Awaish Kumar: Did you capture the the button which says, Easy apply.
98 00:10:24.610 ⇒ 00:10:31.469 Awaish Kumar: But like, was that a big project, or was that a like class project? I just wanna.
99 00:10:32.180 ⇒ 00:10:39.109 sai subhash manam: So I just wanted to, you know, just play around with Linkedin like play around like what? What? This account? So that’s like a personal project.
100 00:10:39.110 ⇒ 00:10:42.690 Awaish Kumar: I wanna understand what you’re doing at your job.
101 00:10:43.440 ⇒ 00:10:45.430 sai subhash manam: Sorry, and.
102 00:10:45.430 ⇒ 00:10:48.630 Awaish Kumar: What are your, what you are actually working with in at your job?
103 00:10:49.860 ⇒ 00:10:51.529 sai subhash manam: Right now as a full stack developer.
104 00:10:51.680 ⇒ 00:10:52.095 Awaish Kumar: Yeah.
105 00:10:53.050 ⇒ 00:10:57.320 sai subhash manam: So basically, my day to day work looks like building a custom docker images.
106 00:10:57.320 ⇒ 00:10:58.000 Awaish Kumar: Any business.
107 00:10:58.000 ⇒ 00:11:01.830 sai subhash manam: And also working with the back end and of end ui.
108 00:11:01.950 ⇒ 00:11:13.030 sai subhash manam: based on the requirements of the user so that we are almost in the production stage. So building individual user interfaces and we’re handling each issue one at a time. Right now.
109 00:11:14.680 ⇒ 00:11:19.970 Awaish Kumar: No, but what exactly like I’m I’m like, I’m not a business.
110 00:11:19.970 ⇒ 00:11:21.299 Awaish Kumar: Okay. I got you. I got you.
111 00:11:21.300 ⇒ 00:11:30.190 Awaish Kumar: I want to understand the your technical architecture, flow and languages, and the tech stack that you’re using.
112 00:11:31.880 ⇒ 00:11:54.780 sai subhash manam: So basically, I’m gonna go with you 1st and then go to the tech stack. So basically, what brain forge does is so it’s a neuroimaging where user can have their data. So with along with the privacy and with the authorization require requirements. So basically, what it does is, you know, it’s very difficult to.
113 00:11:54.810 ⇒ 00:12:04.180 sai subhash manam: you know. Submit the bad jobs and everything for sometime, for a neuroscientist or someone who doesn’t have any idea how the containers work, how the slum architecture works.
114 00:12:04.380 ⇒ 00:12:20.430 sai subhash manam: So what Brainforge access, like an integrated platform where user can upload their data and data, use a required pipeline, get the results with, who are the person they want to share. So for this particular project, the tech stack we are using for the back, using Python Django
115 00:12:20.590 ⇒ 00:12:28.040 sai subhash manam: and Graphql and rest Aps for the communications with the database and react js for the friend.
116 00:12:29.910 ⇒ 00:12:32.909 sai subhash manam: So that’s that we are using right now, and also.
117 00:12:32.910 ⇒ 00:12:38.250 Awaish Kumar: Is that is that data heavy application?
118 00:12:38.460 ⇒ 00:12:39.460 Awaish Kumar: Exactly. It’s like.
119 00:12:39.460 ⇒ 00:12:42.929 sai subhash manam: Data, heavy application, actually, because each.
120 00:12:42.930 ⇒ 00:12:50.239 Awaish Kumar: And how is that like you you mentioned? It’s going to be live soon. That means it’s not live yet.
121 00:12:51.840 ⇒ 00:12:56.399 sai subhash manam: We’re actually at the testing phase right now. So you use. So the tool is used with.
122 00:12:56.400 ⇒ 00:13:03.369 Awaish Kumar: Like. I want to understand what you have built it for, like, how many like you.
123 00:13:04.490 ⇒ 00:13:05.570 sai subhash manam: So we will be handling.
124 00:13:05.570 ⇒ 00:13:12.900 Awaish Kumar: Expected. What was your mind like? How many users are going to use this app like
125 00:13:13.802 ⇒ 00:13:14.980 Awaish Kumar: when it’s when.
126 00:13:14.980 ⇒ 00:13:19.230 sai subhash manam: So on an average day it’s going to be less than 100 users.
127 00:13:19.490 ⇒ 00:13:29.340 sai subhash manam: because only the pis and a bunch of assistants under them are going to use it. Mostly guests will be submitting the jobs and handling the data. The assistants are only
128 00:13:29.590 ⇒ 00:13:34.809 sai subhash manam: will only be accessed only a small set of data set only the one which they require.
129 00:13:35.710 ⇒ 00:13:42.959 sai subhash manam: So, but the data is like each study. Each each study has around, like around, like 50 TB of data.
130 00:13:43.220 ⇒ 00:13:46.050 sai subhash manam: And there are over like 100 that are 100 studies.
131 00:13:46.930 ⇒ 00:13:52.860 Awaish Kumar: And have you worked with the AI like.
132 00:13:53.450 ⇒ 00:13:56.430 sai subhash manam: Yeah, I work directly under the Va. Yes, yes.
133 00:13:57.920 ⇒ 00:14:00.439 Awaish Kumar: I mean, have you built any AI agents or something?
134 00:14:01.310 ⇒ 00:14:04.419 sai subhash manam: Yeah, agents. No. Fortunately I haven’t.
135 00:14:04.590 ⇒ 00:14:10.420 Awaish Kumar: Have you like? Have you any experience with Rnlms Chatgpt, Lambda.
136 00:14:12.280 ⇒ 00:14:18.570 sai subhash manam: So I have an understanding how things work around with it. But I never. I never got the opportunity to just play around with them.
137 00:14:19.510 ⇒ 00:14:21.620 sai subhash manam: So I just created a small.
138 00:14:23.442 ⇒ 00:14:29.029 Awaish Kumar: Okay, so you so right now, like your mo, most of your experiences
139 00:14:29.660 ⇒ 00:14:35.799 Awaish Kumar: around building building an mobile application, and that can
140 00:14:36.790 ⇒ 00:14:50.049 Awaish Kumar: like in general. I just want to understand, like like in terms of like what we have in the role. AI and innovation is mostly we are AI and Automation engineers.
141 00:14:50.170 ⇒ 00:14:55.169 Awaish Kumar: They are responsible for building. For example, AI agents, as I mentioned, so.
142 00:14:55.820 ⇒ 00:15:21.100 Awaish Kumar: And the automation like automating any kind of manual work. For example, as you mentioned, applying to jobs or applying for bids and getting the responses or using some some tools to collect data for different companies around the Internet and then, but then, like like automating everything internal like.
143 00:15:21.740 ⇒ 00:15:25.889 Awaish Kumar: If if anyone is working with the files and like
144 00:15:26.330 ⇒ 00:15:35.094 Awaish Kumar: writing emails, so like, we may be building some agents to help them. Write those emails and build the web platform for them.
145 00:15:36.390 ⇒ 00:15:42.429 Awaish Kumar: so if you could share any of your experience which align with what is what I just said.
146 00:15:44.910 ⇒ 00:16:08.910 sai subhash manam: So like I mentioned before, I work with the I already worked with the Linkedin automation tool. But I also work with, you know. So it’s like a huge project. So initially, it actually extracts the all the latest jobs based on the user keywords which I enter. Like the location, the title of the room, the number of years of experience it requires, like the Linkedin has a filter called
147 00:16:09.579 ⇒ 00:16:13.729 sai subhash manam: you know, it’s like a entry level or intermediate or an experienced role.
148 00:16:13.840 ⇒ 00:16:17.475 sai subhash manam: So the user can actually finally,
149 00:16:18.560 ⇒ 00:16:22.049 sai subhash manam: set these values in a variable and later.
150 00:16:22.650 ⇒ 00:16:35.470 sai subhash manam: the job application tool will actually go to the Linkedin automatically, logins with the user’s credentials. Later, it surely looks for these particular keywords and applies, populates them
151 00:16:36.170 ⇒ 00:16:43.349 sai subhash manam: and goes through all the job listings, extracts each individual one, then later goes to each individual link, extracts the record
152 00:16:43.600 ⇒ 00:16:44.510 sai subhash manam: pins.
153 00:16:44.690 ⇒ 00:16:51.469 sai subhash manam: So it is a quite huge project, and actually aligns with what you have been saying.
154 00:16:52.160 ⇒ 00:16:55.100 sai subhash manam: For the AI part, I actually used a
155 00:16:56.720 ⇒ 00:17:01.560 sai subhash manam: Gpt. 4 point Gpt. Ll Openai
156 00:17:02.280 ⇒ 00:17:08.960 sai subhash manam: api endpoint in order to figure out like what percentage of the job is matching with the and.
157 00:17:09.599 ⇒ 00:17:09.969 Awaish Kumar: Isn’t that.
158 00:17:10.482 ⇒ 00:17:12.020 sai subhash manam: As well. Yeah.
159 00:17:34.150 ⇒ 00:17:41.439 Awaish Kumar: Yeah, sorry. So yeah. like, I, I
160 00:17:42.170 ⇒ 00:17:46.030 Awaish Kumar: like, have, have you used AI in your work, for example, like
161 00:17:47.040 ⇒ 00:17:50.309 Awaish Kumar: doing your development work with the help of AI.
162 00:17:51.050 ⇒ 00:17:58.289 sai subhash manam: Yeah, I did use. Because in my current work, I frequently use a because I’m completely new to the concept
163 00:17:58.600 ⇒ 00:18:16.640 sai subhash manam: imaging terms. Because when I’m building custom, I don’t have much instructions like, I need to know, like what each individual data type is doing so for the process in order to get an overview of what this particular file is like, what exactly we are working on. I just use AI for these type of things
164 00:18:17.560 ⇒ 00:18:19.199 sai subhash manam: and also for the same.
165 00:18:19.200 ⇒ 00:18:24.330 Awaish Kumar: More requirement, like, what I understand is, you have used AI to
166 00:18:24.660 ⇒ 00:18:32.869 Awaish Kumar: to get more context and the requirements for for the things you’re working with but have you use it to develop something like
167 00:18:34.550 ⇒ 00:18:42.820 Awaish Kumar: like, Use AI to develop a web page, or what kind of feature you are working on how you use AI to help you build that feature.
168 00:18:43.160 ⇒ 00:18:49.899 sai subhash manam: Exactly. I use sometimes. Yeah, I actually use sometimes, in order to get few syntaxes or any ideas.
169 00:18:49.900 ⇒ 00:18:51.289 Awaish Kumar: What did you do? Mr President.
170 00:18:52.770 ⇒ 00:18:59.073 sai subhash manam: Suppose if I’m working on a front end part like, what is the syntax in order to get a square box with,
171 00:18:59.970 ⇒ 00:19:04.319 sai subhash manam: you know circular edges and this type of colors. So just go
172 00:19:04.911 ⇒ 00:19:07.639 sai subhash manam: Chat Gpt, or any of the latest Llms.
173 00:19:08.150 ⇒ 00:19:10.283 sai subhash manam: So just give the prompt
174 00:19:10.970 ⇒ 00:19:16.525 sai subhash manam: of saying like I need. I’m working on this particular project. I need a front end
175 00:19:17.460 ⇒ 00:19:22.500 sai subhash manam: using these particular features and the response going to proceed from there.
176 00:19:24.031 ⇒ 00:19:30.390 Awaish Kumar: And apart from that, have you calm?
177 00:19:31.680 ⇒ 00:19:40.899 Awaish Kumar: Yeah, like you? How would you rate yourself in calm fights and like, and.
178 00:19:41.770 ⇒ 00:19:43.089 sai subhash manam: In terms of python.
179 00:19:43.090 ⇒ 00:19:43.760 Awaish Kumar: Thank you.
180 00:19:43.760 ⇒ 00:19:58.649 sai subhash manam: Feel pretty confident. So I’ve been throughout my career in Python itself. I do have under. I do have understanding, working knowledge, working with C. And Java as well, but mostly even during my projects and during my.
181 00:20:00.090 ⇒ 00:20:02.198 Awaish Kumar: What is the difference between
182 00:20:03.690 ⇒ 00:20:07.530 Awaish Kumar: Java programming language and the Python programming language?
183 00:20:07.940 ⇒ 00:20:09.870 Awaish Kumar: What is the core differences.
184 00:20:11.210 ⇒ 00:20:19.320 sai subhash manam: Well, of course, the 1st thing to my mind, is the syntax. The python syntax is like completely, you know.
185 00:20:19.680 ⇒ 00:20:21.550 sai subhash manam: a simple and user, friendly.
186 00:20:22.660 ⇒ 00:20:36.242 sai subhash manam: And so both are like object oriented programming language itself, and both are you various
187 00:20:37.050 ⇒ 00:20:40.800 sai subhash manam: task? I couldn’t find actually a major difference between them.
188 00:20:41.360 ⇒ 00:20:47.720 Awaish Kumar: Is there any key difference between them? How they, for example, execute the code.
189 00:20:48.430 ⇒ 00:21:10.109 sai subhash manam: So basically, python is like it. When we are executing the code, it goes line by line, line by line, line by line. So it goes like a sequential way when it comes to when it is come, when it comes to Java. So all the code is predefined, converted into an intermediate form. Later, this intermediate is actually executed by the compiler.
190 00:21:13.675 ⇒ 00:21:18.650 Awaish Kumar: So like, okay. And you mentioned, you have.
191 00:21:18.650 ⇒ 00:21:20.239 sai subhash manam: I don’t exactly remember the time.
192 00:21:21.250 ⇒ 00:21:21.810 sai subhash manam: Yes.
193 00:21:22.452 ⇒ 00:21:24.379 Awaish Kumar: So and so.
194 00:21:24.780 ⇒ 00:21:29.579 Awaish Kumar: So, you know the concept of memory management too late and.
195 00:21:34.120 ⇒ 00:21:37.859 sai subhash manam: So is there in particular you’re looking for right now, like.
196 00:21:38.040 ⇒ 00:21:43.139 Awaish Kumar: Like, how, how like Python manages its memory. Like we write code.
197 00:21:43.270 ⇒ 00:21:46.460 Awaish Kumar: we, we define variables, lists, and everything.
198 00:21:46.680 ⇒ 00:21:48.790 Awaish Kumar: So how? Basically
199 00:21:52.537 ⇒ 00:21:58.569 Awaish Kumar: like, it manages the memory like it has. We have limited memory assigned to our process
200 00:21:58.900 ⇒ 00:22:01.550 Awaish Kumar: python process, which is going to run our script.
201 00:22:01.670 ⇒ 00:22:05.290 Awaish Kumar: and we are defining variable and and things like that.
202 00:22:05.440 ⇒ 00:22:11.520 Awaish Kumar: so how it can manage its memory, for for inside its browser.
203 00:22:14.470 ⇒ 00:22:17.160 sai subhash manam: To be honest, I don’t have any idea about the question.
204 00:22:17.160 ⇒ 00:22:23.510 Awaish Kumar: Example, like to define the type of variables, how they are going to be stored.
205 00:22:24.600 ⇒ 00:22:31.999 Awaish Kumar: Like, for example, if I okay, can you write a code, for example, which can give you an out of memory error.
206 00:22:34.070 ⇒ 00:22:36.190 sai subhash manam: Oh, out of memory error.
207 00:22:41.240 ⇒ 00:22:43.320 sai subhash manam: So, Lisa?
208 00:22:43.710 ⇒ 00:22:53.310 sai subhash manam: Oh, so usually in other languages, out of memory error. And we like years of everything.
209 00:22:53.430 ⇒ 00:23:03.799 sai subhash manam: Okay in python. Exactly, I’m sure, because we use they don’t have anything like a preoccupied memory just dynamically allocates the memory.
210 00:23:03.800 ⇒ 00:23:05.480 Awaish Kumar: Yeah, but it still.
211 00:23:06.430 ⇒ 00:23:15.790 Awaish Kumar: like every python process, you are going to create right? That will have some memory assigned to it, some limited memory.
212 00:23:15.890 ⇒ 00:23:19.480 Awaish Kumar: and if it exceeds that.
213 00:23:19.720 ⇒ 00:23:31.743 Awaish Kumar: So you have mentioned, you have got a lot of data. But like, if you have worked with processing a lot of data then like this, this should be the 1st concern. How are you going to
214 00:23:32.370 ⇒ 00:23:46.416 Awaish Kumar: process everything. In a for example, you have 20 Gb, Csv file. And if I want to write, want you to write a python code which reads this Csv file, and then,
215 00:23:47.270 ⇒ 00:23:50.969 Awaish Kumar: adds a column, for example, how would you do that.
216 00:23:53.300 ⇒ 00:23:59.210 sai subhash manam: So at 20 V of a Csv file, okay.
217 00:23:59.210 ⇒ 00:24:25.330 Awaish Kumar: Memory is 8 gb, like we have. The the computer has 8 Gb. Memory, but the process python process got like only, for example, 2 Gb’s assigned right. And in that 2 Gb, you have to process a Csv file and add a new column, which is basically 20 Gb’s size, like the size of that file is 20. Gb, so how would you write it, for example, this, this
218 00:24:25.980 ⇒ 00:24:29.440 Awaish Kumar: snippet of python code, like what exactly
219 00:24:29.690 ⇒ 00:24:32.749 Awaish Kumar: will be the code to approach that.
220 00:24:34.720 ⇒ 00:24:43.129 sai subhash manam: Well, I’m just going to give you the basic task. I’m gonna do so initially. Just import the pandas pandas package from
221 00:24:43.840 ⇒ 00:24:51.030 sai subhash manam: python later read the Csv frame and import a new column that’s usually works.
222 00:24:51.030 ⇒ 00:24:52.220 Awaish Kumar: How would you?
223 00:24:52.830 ⇒ 00:25:01.530 Awaish Kumar: But how are you going to load a data frame of 20 Gb’s of data into a 2 Gb of memory?
224 00:25:03.950 ⇒ 00:25:05.860 sai subhash manam: Interesting question.
225 00:25:10.610 ⇒ 00:25:12.440 Awaish Kumar: Oh, okay, yeah, so, so.
226 00:25:12.440 ⇒ 00:25:13.440 sai subhash manam: I have no idea.
227 00:25:13.440 ⇒ 00:25:16.249 Awaish Kumar: Yeah, so we can pass that like, okay.
228 00:25:16.360 ⇒ 00:25:20.770 Awaish Kumar: apart from that, what are the context managers in python.
229 00:25:22.350 ⇒ 00:25:23.969 sai subhash manam: Context managers.
230 00:25:24.650 ⇒ 00:25:25.270 Awaish Kumar: Yeah.
231 00:25:26.630 ⇒ 00:25:27.330 sai subhash manam: Oh!
232 00:25:27.330 ⇒ 00:25:30.320 Awaish Kumar: Have you worked with files? Have you read any file in python.
233 00:25:32.460 ⇒ 00:25:34.450 sai subhash manam: Yeah, we actually, I don’t exactly remember.
234 00:25:34.450 ⇒ 00:25:39.609 Awaish Kumar: How would you, for example, if I have a text file, how would you open it in Python.
235 00:25:43.010 ⇒ 00:25:43.889 Awaish Kumar: Just open and.
236 00:25:43.890 ⇒ 00:25:44.670 sai subhash manam: Excellent.
237 00:25:45.570 ⇒ 00:25:46.390 Awaish Kumar: Yeah.
238 00:25:46.390 ⇒ 00:25:52.970 sai subhash manam: So reopen by file, command and print line by.
239 00:25:53.510 ⇒ 00:25:55.360 sai subhash manam: I need to go through each of them.
240 00:25:55.360 ⇒ 00:26:00.039 Awaish Kumar: That’s my question. How would you read it? Like the what exactly you would write, for example.
241 00:26:01.850 ⇒ 00:26:03.960 Awaish Kumar: But the syntax.
242 00:26:04.650 ⇒ 00:26:09.300 sai subhash manam: Ds file or something. I don’t exactly remember the. So I’m gonna use it for it.
243 00:26:10.250 ⇒ 00:26:16.200 Awaish Kumar: Yeah, like, so like, it’s not a like a very complex thing. It’s just one
244 00:26:16.720 ⇒ 00:26:19.800 Awaish Kumar: single liner to read a 55.
245 00:26:19.800 ⇒ 00:26:20.770 sai subhash manam: Yeah. So
246 00:26:22.050 ⇒ 00:26:27.570 sai subhash manam: so I do remember, like a model. And I do remember it. But exactly, I don’t remember like exact keywords. We.
247 00:26:27.570 ⇒ 00:26:28.389 Awaish Kumar: You don’t know the point.
248 00:26:29.013 ⇒ 00:26:30.259 sai subhash manam: As a.
249 00:26:32.400 ⇒ 00:26:39.810 Awaish Kumar: Okay. Have you? Ever used with keyword?
250 00:26:40.870 ⇒ 00:26:41.640 sai subhash manam: Width.
251 00:26:41.640 ⇒ 00:26:42.639 Awaish Kumar: It’s quite good.
252 00:26:46.370 ⇒ 00:26:48.930 Awaish Kumar: Which keyboard WITH.
253 00:26:53.570 ⇒ 00:26:55.920 sai subhash manam: I don’t exactly remember using the link.
254 00:26:55.920 ⇒ 00:26:58.819 Awaish Kumar: For example, if I ask you to write a follow up, you would
255 00:26:58.920 ⇒ 00:27:02.789 Awaish Kumar: right for, and then something right great for.
256 00:27:02.790 ⇒ 00:27:03.110 sai subhash manam: Yes.
257 00:27:03.110 ⇒ 00:27:06.820 Awaish Kumar: Word, and in the keyword. Similarly.
258 00:27:06.820 ⇒ 00:27:07.170 sai subhash manam: Yes.
259 00:27:07.170 ⇒ 00:27:09.980 Awaish Kumar: Wit is a key word, and it is used for some.
260 00:27:11.400 ⇒ 00:27:16.849 sai subhash manam: Yeah, I understand with is a key. But I don’t exactly remember how I’m going to use with.
261 00:27:17.610 ⇒ 00:27:18.510 Awaish Kumar: Okay?
262 00:27:22.060 ⇒ 00:27:32.139 Awaish Kumar: Okay? And then, and python, like, for example, okay, yeah.
263 00:27:33.470 ⇒ 00:27:39.700 Awaish Kumar: do you have enough experience with C, or mostly with python?
264 00:27:39.700 ⇒ 00:27:43.770 sai subhash manam: I have most experience with Bithana. Actually.
265 00:27:44.950 ⇒ 00:27:50.560 Awaish Kumar: Okay, what? Let’s ask.
266 00:27:53.270 ⇒ 00:28:00.740 Awaish Kumar: Oh, okay, like, how do you know the concept like you mentioned about object oriented?
267 00:28:00.940 ⇒ 00:28:05.080 Awaish Kumar: What is object oriented, and how, why we use that.
268 00:28:07.060 ⇒ 00:28:17.969 sai subhash manam: Well object oriented programming. We have like a concepts in it like abstraction and inheritance and
269 00:28:19.950 ⇒ 00:28:25.360 sai subhash manam: abstraction, inheritance and polymorphism.
270 00:28:26.450 ⇒ 00:28:32.725 sai subhash manam: I don’t. I’m sorry I don’t. I haven’t gone through it again in a while, but
271 00:28:34.030 ⇒ 00:28:39.990 Awaish Kumar: Yeah, but by 10 as the good fun
272 00:28:40.910 ⇒ 00:28:53.200 Awaish Kumar: like in the inherit, like in the object Orient program programming, the the fundamental concept is of abstraction, and how you achieve it is by using inheritance.
273 00:28:53.410 ⇒ 00:28:55.799 Awaish Kumar: The concept of inheritance.
274 00:28:56.730 ⇒ 00:28:57.900 sai subhash manam: And we don’t need to hit the call.
275 00:28:57.900 ⇒ 00:29:04.650 Awaish Kumar: Then the there comes the polymorphism, and the polymorphism is also implemented using the concept of inheritance.
276 00:29:09.210 ⇒ 00:29:12.349 Awaish Kumar: Then there’s 1 more concept. It’s called composition.
277 00:29:12.950 ⇒ 00:29:15.400 Awaish Kumar: So these are the basic building blocks of
278 00:29:15.680 ⇒ 00:29:17.300 Awaish Kumar: from the object code in program.
279 00:29:17.636 ⇒ 00:29:18.980 sai subhash manam: Forgot their company. Yeah.
280 00:29:18.980 ⇒ 00:29:23.673 Awaish Kumar: I mean so if for example,
281 00:29:25.390 ⇒ 00:29:27.899 Awaish Kumar: Have you ever used a function?
282 00:29:28.120 ⇒ 00:29:33.550 Awaish Kumar: Oh, how do you write a function in python and pass some parameters, for example.
283 00:29:34.900 ⇒ 00:29:39.129 sai subhash manam: So I’m just going to create a phone using the Dev keyword.
284 00:29:40.430 ⇒ 00:29:45.590 Awaish Kumar: For example, write a function to sum 2 integers.
285 00:29:46.380 ⇒ 00:29:51.710 sai subhash manam: Okay, does it take any of the arguments like, yeah, does the function of any parameter.
286 00:29:51.710 ⇒ 00:29:57.329 Awaish Kumar: 2 to explore A and B, and then sums it and returns it.
287 00:29:58.440 ⇒ 00:30:11.079 sai subhash manam: Write a function called Def add, and we takes 2 arguments A and B vectors, and for the function starts with the invitation. Yes, we can. Just one line of code called written.
288 00:30:11.080 ⇒ 00:30:11.690 Awaish Kumar: Okay.
289 00:30:11.810 ⇒ 00:30:17.409 Awaish Kumar: But thank you. My next question is, if we have same function.
290 00:30:17.780 ⇒ 00:30:32.360 Awaish Kumar: add function. And I I’m I was like, we were passing 2 only 2 parameters. Now, if you, for example I want to pass I want to leave it to to the user.
291 00:30:32.500 ⇒ 00:30:35.212 Awaish Kumar: and he can pass as many as
292 00:30:37.500 ⇒ 00:30:39.183 Awaish Kumar: as you want, like as
293 00:30:39.760 ⇒ 00:30:43.390 Awaish Kumar: many the parameter as you want.
294 00:30:43.720 ⇒ 00:30:50.650 Awaish Kumar: he can pass on to this function, and we can sum all of them, and return the final value
295 00:30:52.310 ⇒ 00:30:55.250 Awaish Kumar: instead of suggest having an A and B.
296 00:30:55.490 ⇒ 00:31:03.070 Awaish Kumar: I can send, for example, say 30 different parameters.
297 00:31:03.430 ⇒ 00:31:06.679 Awaish Kumar: hour integers, and I can submit and then return the result.
298 00:31:06.870 ⇒ 00:31:09.620 Awaish Kumar: So how would you now modify this function?
299 00:31:10.940 ⇒ 00:31:14.560 sai subhash manam: So basically whenever so this is my, so.
300 00:31:14.560 ⇒ 00:31:15.370 Awaish Kumar: Not sure.
301 00:31:15.610 ⇒ 00:31:23.619 sai subhash manam: So whenever there are, if we pass less or more arguments than we have actually defined in the function, we will be automatic error.
302 00:31:24.150 ⇒ 00:31:30.480 sai subhash manam: But I’m not really sure how exactly I’m gonna handle. When we when the user gonna send 30 of the parameters to the function.
303 00:31:30.480 ⇒ 00:31:31.770 Awaish Kumar: No, no! Do that.
304 00:31:31.770 ⇒ 00:31:34.060 sai subhash manam: Parameters. So we need to cause.
305 00:31:34.060 ⇒ 00:31:35.859 Awaish Kumar: Yeah, I’m not. I’m not concerned.
306 00:31:35.860 ⇒ 00:31:36.510 sai subhash manam: Great.
307 00:31:36.510 ⇒ 00:31:53.200 Awaish Kumar: I’m not concerned about how user gives. An input. I’m concerned about this function has an ability to to accept all those parameters and sums it and returns the value. Just, I’m focusing on the implementation of this function.
308 00:31:55.080 ⇒ 00:31:56.946 sai subhash manam: Were you on the function?
309 00:31:59.630 ⇒ 00:32:01.729 sai subhash manam: in order to accept the parameter? And
310 00:32:04.970 ⇒ 00:32:06.240 sai subhash manam: maybe
311 00:32:06.380 ⇒ 00:32:16.830 sai subhash manam: I’m thinking of an odd way. If there’s a better way, I’m not really sure but my thought, this is something like this. So we are still using 2 parameters called sum current sum. And
312 00:32:17.170 ⇒ 00:32:22.730 sai subhash manam: so so whenever the you know.
313 00:32:22.730 ⇒ 00:32:24.999 Awaish Kumar: The user sends a new.
314 00:32:25.000 ⇒ 00:32:25.320 sai subhash manam: Yeah.
315 00:32:25.320 ⇒ 00:32:30.739 Awaish Kumar: Now you you want to call this function multiple times in in some kind of a loop.
316 00:32:30.900 ⇒ 00:32:31.959 Awaish Kumar: I’m glad you’re finally.
317 00:32:31.960 ⇒ 00:32:33.679 sai subhash manam: Like a recursion, or something like exactly.
318 00:32:33.680 ⇒ 00:32:34.350 Awaish Kumar: Good.
319 00:32:34.930 ⇒ 00:32:36.170 Awaish Kumar: Okay, you know.
320 00:32:36.290 ⇒ 00:32:42.821 Awaish Kumar: Yeah, you’re just think like making it a lot more complex than it is like.
321 00:32:43.230 ⇒ 00:32:46.159 sai subhash manam: I think there’s a better way. But yeah, I don’t exactly remember.
322 00:32:46.160 ⇒ 00:33:02.139 Awaish Kumar: You know, you can use, for example, a for loop, basically and call this function multiple times with a with a previous sum, and then get the values. I know I there’s no need to do all of that like we can have in a list and just sum it up like I’m just making up a scenario.
323 00:33:02.340 ⇒ 00:33:06.530 Awaish Kumar: Sometimes we get some use cases in our in our
324 00:33:06.950 ⇒ 00:33:07.680 sai subhash manam: Okay, yeah.
325 00:33:07.680 ⇒ 00:33:11.979 sai subhash manam: You are not really sure of how many arguments are going to come.
326 00:33:12.447 ⇒ 00:33:18.689 Awaish Kumar: To my function might be 2 might be 3 might be 5. How we are going to that handle, that variability.
327 00:33:19.090 ⇒ 00:33:23.529 sai subhash manam: Yes, we can just use a list like you mentioned. So, user can include all numbers.
328 00:33:23.530 ⇒ 00:33:25.500 sai subhash manam: Yeah, all the parameters.
329 00:33:26.030 ⇒ 00:33:28.120 sai subhash manam: The user can.
330 00:33:28.120 ⇒ 00:33:44.969 Awaish Kumar: That was not a I’m just saying that that, like the better ways of handling this exact scenario are different. But I’m I’m not focusing on actually summing things. I’m focusing my target is to get a function which can accept variable number of parameters
331 00:33:45.360 ⇒ 00:33:48.020 Awaish Kumar: which we are. We don’t know how many it can be.
332 00:33:48.750 ⇒ 00:33:52.510 sai subhash manam: Okay, I’m not gonna waste your time. I have no idea, like
333 00:33:53.430 ⇒ 00:33:55.660 sai subhash manam: how I can do that. Yeah.
334 00:33:56.760 ⇒ 00:34:04.740 Awaish Kumar: Have you ever heard of? Something like like what Lucas.
335 00:34:07.090 ⇒ 00:34:11.970 sai subhash manam: Yeah, I heard about it, but never had the opportunity to use them. Actually.
336 00:34:12.469 ⇒ 00:34:13.674 Awaish Kumar: Okay.
337 00:34:15.520 ⇒ 00:34:18.749 sai subhash manam: We’re used to this. Okay, I’m gonna review some decisions.
338 00:34:18.750 ⇒ 00:34:19.569 Awaish Kumar: That’s okay.
339 00:34:19.800 ⇒ 00:34:21.150 Awaish Kumar: So.
340 00:34:21.259 ⇒ 00:34:21.959 sai subhash manam: Okay.
341 00:34:22.199 ⇒ 00:34:27.619 Awaish Kumar: Apart from that, what is list? Comprehension in Python.
342 00:34:29.300 ⇒ 00:34:30.570 sai subhash manam: List. Comprehension?
343 00:34:41.360 ⇒ 00:34:43.440 sai subhash manam: Is it like appending tool list or something.
344 00:34:44.300 ⇒ 00:34:54.875 Awaish Kumar: No in the python. Simple, the basic python code. If if I want to to write some
345 00:34:58.230 ⇒ 00:35:03.200 Awaish Kumar: I give you a list offer
346 00:35:03.860 ⇒ 00:35:09.120 Awaish Kumar: some integer values, and I would like you to square them
347 00:35:09.230 ⇒ 00:35:13.329 Awaish Kumar: and store it. Store them in a list.
348 00:35:14.360 ⇒ 00:35:15.130 sai subhash manam: And immune.
349 00:35:15.130 ⇒ 00:35:17.520 Awaish Kumar: Better list. Right? So how would you do that?
350 00:35:17.520 ⇒ 00:35:18.579 sai subhash manam: Or the you know.
351 00:35:18.580 ⇒ 00:35:18.960 Awaish Kumar: Hello! There!
352 00:35:22.170 ⇒ 00:35:27.029 sai subhash manam: So we can just use the it’s comprehension.
353 00:35:28.840 ⇒ 00:35:31.658 sai subhash manam: There might be a default functions for doing them. But
354 00:35:31.940 ⇒ 00:35:32.590 Awaish Kumar: I don’t know.
355 00:35:33.640 ⇒ 00:35:41.229 Awaish Kumar: I don’t need any default. I was just write it right. It’s not that difficult to write that. How would you write that code.
356 00:35:42.130 ⇒ 00:35:43.189 Awaish Kumar: iterate over.
357 00:35:43.190 ⇒ 00:35:44.219 sai subhash manam: Like, I’m gonna create.
358 00:35:47.760 ⇒ 00:35:48.620 Awaish Kumar: Then.
359 00:35:48.620 ⇒ 00:35:49.419 sai subhash manam: For this particular one.
360 00:35:49.910 ⇒ 00:35:59.279 sai subhash manam: I’m going to create a new list. So suppose the current elements are in the list called A, and I’m going to create a new list called B. So the B goes to
361 00:35:59.590 ⇒ 00:36:00.790 sai subhash manam: of
362 00:36:05.276 ⇒ 00:36:10.930 sai subhash manam: Without a for loop. If you’re using A for loop, I’m just going to do a for loop, for I in the range of list.
363 00:36:11.560 ⇒ 00:36:17.321 sai subhash manam: if I study of, I can do something like that. But without using any far loops or something like that
364 00:36:18.570 ⇒ 00:36:20.789 Awaish Kumar: Yeah, we are going to use follow.
365 00:36:21.390 ⇒ 00:36:22.560 sai subhash manam: Okay.
366 00:36:23.200 ⇒ 00:36:28.060 Awaish Kumar: We are going to use follow, but know
367 00:36:28.460 ⇒ 00:36:33.420 Awaish Kumar: so normally like, what you are saying is, just write a for loop, and then
368 00:36:33.600 ⇒ 00:36:37.009 Awaish Kumar: in the second line you write something.
369 00:36:37.120 ⇒ 00:36:42.269 Awaish Kumar: Thanks for the call manager of A for loop, and then do write some
370 00:36:42.450 ⇒ 00:36:45.749 Awaish Kumar: multiplic multiplication of items, and then store
371 00:36:47.123 ⇒ 00:36:49.459 Awaish Kumar: the list right, append it, or whatever.
372 00:36:50.140 ⇒ 00:36:57.979 Awaish Kumar: But instead of doing that, can we write up for single liner without using this column for function? For blue?
373 00:36:58.590 ⇒ 00:37:03.499 Awaish Kumar: That’s basically the concept with comprehension. You can visit. You can look for it.
374 00:37:04.360 ⇒ 00:37:05.040 sai subhash manam: Okay.
375 00:37:05.360 ⇒ 00:37:06.270 Awaish Kumar: Okay,
376 00:37:08.150 ⇒ 00:37:12.650 Awaish Kumar: So yeah, that’s mainly it for me. Oh.
377 00:37:12.680 ⇒ 00:37:13.460 sai subhash manam: Okay.
378 00:37:13.820 ⇒ 00:37:17.090 Awaish Kumar: If you have any other questions like you may ask.
379 00:37:17.960 ⇒ 00:37:18.499 Awaish Kumar: There we go.
380 00:37:18.842 ⇒ 00:37:26.729 sai subhash manam: Sure thing. So I was actually expecting this more like initial Hr interview. So I was actually preparing for the Hr stuff. Actually.
381 00:37:27.450 ⇒ 00:37:29.390 sai subhash manam: So I haven’t got.
382 00:37:29.590 ⇒ 00:37:32.790 sai subhash manam: So I’m not yeah anything.
383 00:37:34.390 ⇒ 00:37:37.705 sai subhash manam: So that’s the 1st thing I want to say. The next thing is,
384 00:37:38.170 ⇒ 00:37:41.320 sai subhash manam: I do have a couple of questions like, what makes
385 00:37:41.590 ⇒ 00:37:55.590 sai subhash manam: to work with brain foods right now, it’s a startup enrollment. I think you have around like 10 years of or around 8 and 8 to 10 years of experience right now, like, why do you want to work in a startup environment rather than working in the regions like Amazon or some other company?
386 00:37:56.590 ⇒ 00:37:58.240 Awaish Kumar: I would. I want to work.
387 00:37:59.380 ⇒ 00:38:02.639 Awaish Kumar: Okay, I I would love to work. I just
388 00:38:02.760 ⇒ 00:38:20.009 Awaish Kumar: like working. I it just depends on how how much you wanna put in the efforts and how how much you want to stretch yourself in my entire career. Most of the time I have worked with the startups for me.
389 00:38:21.160 ⇒ 00:38:22.170 sai subhash manam: Oh, okay.
390 00:38:24.580 ⇒ 00:38:26.190 sai subhash manam: And the next question
391 00:38:26.610 ⇒ 00:38:32.410 sai subhash manam: is like, What are the current challenges? Brain forge is actually facing. So as a startup like, what are the current?
392 00:38:32.630 ⇒ 00:38:34.099 sai subhash manam: Yes, it is fixed.
393 00:38:34.100 ⇒ 00:38:36.959 Awaish Kumar: The current challenges. Yeah, like.
394 00:38:37.330 ⇒ 00:38:48.544 Awaish Kumar: So I don’t know. Like brain force is as a company was doing a lot of things. And there must be challenges everywhere. Right?
395 00:38:49.360 ⇒ 00:38:51.519 Awaish Kumar: everybody. With this Booker, like
396 00:38:52.990 ⇒ 00:39:13.794 Awaish Kumar: we we have people working in different sales, marketing, engineering team. And then we have the AI team, and then we have operations, everything. So I I don’t think we are facing any specific, any any challenge, right? We that Brainford is doing good. We have a lot of clients. We have a lot of
397 00:39:14.720 ⇒ 00:39:21.830 Awaish Kumar: good people who are working here. We are like good, very good engineers and developers here.
398 00:39:21.940 ⇒ 00:39:26.729 Awaish Kumar: and they are all collaborative. So in a sense, we
399 00:39:27.578 ⇒ 00:39:29.971 Awaish Kumar: are doing a lot better.
400 00:39:30.670 ⇒ 00:39:36.930 Awaish Kumar: And yeah, that’s what I could see right? Online.
401 00:39:37.030 ⇒ 00:39:38.060 Awaish Kumar: Hi.
402 00:39:38.577 ⇒ 00:39:52.090 Awaish Kumar: yeah, yeah. But we, we are as we are consulting firm. So we are like hiring every time we are open for opportunities. That would be. I don’t know if we see the challenge or a or opportunity. But yeah, that’s that’s it, is.
403 00:39:53.760 ⇒ 00:39:55.149 sai subhash manam: Hmm! Interesting.
404 00:39:56.560 ⇒ 00:40:04.650 sai subhash manam: Alright. And I just have one last question. So in the job description, there’s a dumb oh.
405 00:40:05.580 ⇒ 00:40:08.890 sai subhash manam: flexible work, work hours like, how exactly is.
406 00:40:10.040 ⇒ 00:40:11.050 Awaish Kumar: Sorry. Sorry.
407 00:40:11.830 ⇒ 00:40:13.119 Awaish Kumar: What’s the question?
408 00:40:13.120 ⇒ 00:40:18.530 sai subhash manam: Description in the job description I’ve gone through like, what are the benefits of working with
409 00:40:19.060 ⇒ 00:40:25.881 sai subhash manam: so like one of the advantages was like flexible hours like how exactly is like flexible working at.
410 00:40:26.260 ⇒ 00:40:34.080 Awaish Kumar: But ours means you can work on your own time zone. Basically, that is what it means.
411 00:40:35.190 ⇒ 00:40:35.580 sai subhash manam: Oh!
412 00:40:35.580 ⇒ 00:40:47.609 Awaish Kumar: So if you wanna, it’s like, there are 2 things. If you wanna submit for the offers to different type types of opportunities, it can be full time. It can be part time if we need your resources.
413 00:40:50.091 ⇒ 00:40:51.818 Awaish Kumar: Like I I can
414 00:40:52.780 ⇒ 00:41:14.780 Awaish Kumar: approach you. And then, for example, depending on your availability like, if you wanna join us as a full time or a part time, we can make that decision together. That’s number point number one in terms of what flexible hour it can be. Second is how you work like reinforge is remote. As I mentioned, employees are everywhere around the world, and we don’t have any
415 00:41:14.850 ⇒ 00:41:24.000 Awaish Kumar: specific time zone where you work like. Obviously as a consultancy firm. We have clients coming in in our meetings, and
416 00:41:24.160 ⇒ 00:41:37.329 Awaish Kumar: I think some like we have some important internal meetings where where the presence is is required. That’s when you need to be there. Maybe it’s 1 h meeting or 2 h or 3 h, whatever it is.
417 00:41:37.470 ⇒ 00:41:44.449 Awaish Kumar: But apart from that, when you work, how you work is, is up to the employee itself to manage.
418 00:41:45.800 ⇒ 00:41:46.200 sai subhash manam: Okay.
419 00:41:47.600 ⇒ 00:41:51.460 sai subhash manam: Alright, that’s everything. I just have one last point to add from myself.
420 00:41:51.780 ⇒ 00:42:20.249 sai subhash manam: So I’m very much work with a company like brain force like, because I feel satisfied with my answers for the questions. But I still, and I’m a quick learner right now. So I’m looking for an opportunity where I actually can work with the latest disease, you know, either like a full time employer or less like a part time employees, so that I get the latest exposure, like, what’s the world is going to use? Like with the consulting firm, I get those opportunity.
421 00:42:20.650 ⇒ 00:42:23.960 sai subhash manam: Yeah, that’s everything I wanna say right now.
422 00:42:24.890 ⇒ 00:42:33.130 Awaish Kumar: Okay, thank you. Yeah, thank you for taking the time. It was nice conversation. And at last, note, I would just say that like
423 00:42:33.711 ⇒ 00:42:38.129 Awaish Kumar: our like, the Rico from our operations team is going to
424 00:42:38.290 ⇒ 00:42:44.900 Awaish Kumar: get in touch with you for next steps. So I’m going to submit my feedback today, and then they will plan
425 00:42:45.070 ⇒ 00:42:47.529 Awaish Kumar: to send you the next steps.
426 00:42:47.750 ⇒ 00:42:50.110 Awaish Kumar: Maybe in this week or early next week.
427 00:42:51.430 ⇒ 00:42:57.119 sai subhash manam: Okay, so like, what are the next steps? So is it going to be another round of technical interview, like a Hr interview, like, what’s going to be.
428 00:42:57.120 ⇒ 00:43:02.529 Awaish Kumar: I’m not sure, like Rico is going to tell you about that. I don’t know. If, is it your 1st interview.
429 00:43:03.350 ⇒ 00:43:05.240 sai subhash manam: Yeah, this is my 1st interview. Actually.
430 00:43:05.240 ⇒ 00:43:13.609 Awaish Kumar: Yeah, obviously, it can be an interview with our oh, like the
431 00:43:14.470 ⇒ 00:43:19.669 Awaish Kumar: Operations lead, or maybe with someone the CEO for
432 00:43:19.950 ⇒ 00:43:27.879 Awaish Kumar: for more like behavioral questions or something like that. So it can be anything. But he’s going to let flow like you can ask clarifications
433 00:43:28.318 ⇒ 00:43:36.590 Awaish Kumar: clarification questions in your email. If he sends you something for next step, you can. If if that’s something is not clear, you can ask right
434 00:43:36.730 ⇒ 00:43:41.219 Awaish Kumar: what what this interview is going to be what it is about, or things like that. You can do that.
435 00:43:42.300 ⇒ 00:43:43.170 sai subhash manam: Alright!
436 00:43:43.340 ⇒ 00:43:43.966 Awaish Kumar: Thank you.
437 00:43:45.040 ⇒ 00:43:46.620 sai subhash manam: And thank you very much. Have a nice one.