- Interesting Data Gigs by Marcos Ortiz
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- Interesting Data Gigs # 35: Get a job at NVIDIA ASAP
Interesting Data Gigs # 35: Get a job at NVIDIA ASAP
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Hello, Data Geek.
Today I want to give you some quick advice here: Use a “pick and shovel approach” to your job search today.
I know you should be wondering what I mean by that, so let me explain it.
A “pick and shovel approach” to job search is very simple:
Take a role in a company where its services are foundational for other companies, where its services are booming and growing every single month.
Of course, there are some exceptions to this rule, especially after the recent layoffs at Amazon Web Services, Meta, IBM’s Red Hat, and many others.
Many companies are pivoting their services to AI in some form, and I firmly believe that the best company positioned to grow exponentially from today to the future is one and one only: NVIDIA.
If you read any news related to AI, all paths are redirected to Nvidia in some way.
And if you read about every AI partnership, Nvidia is present in some form:
And this is just the beginning. The potential is there.
So: GET A JOB AT NVIDIA ASAP IF YOU HAVE THE CHANCE.
First things, first: Why NVIDIA, why now? 3 Things to do
It’s just a matter of perfect timing, but Jensen Huang and his team at NVIDIA have worked on this for more than 20 years in the making.
They have taken the right steps to be the leader they are today.
I don’t want to tell the whole story about NVIDIA because there are better resources for that.
So, I will give you three core recommendations here.
First, you must listen to/watch the NVIDIA-focused episode in the Acquired FM podcast, hosted by Ben Gilbert and David Rosenthal.
These guys made an outstanding job explaining why NVIDIA is a leader in Accelerated Computing as Jensen calls it.
So, my first recommendation if you want to be part of the company, listen to or watch this episode and take notes about it:
The second recommendation is to listen to/watch this recent conversation between Elad Gil, Sarah Guo, and Jensen Huang.
Jensen gave a lot of tips there, and you feel listening to this conversation that he knows not only his company in and out, but he is an industry student as well, and I strongly believe this is a fundamental skill inside NVIDIA.
Why?
Because the company works with so many different organizations from a large scope of different challenging fields like LLMs, protein engineering, life sciences, and more.
Watch it on YouTube, or listen to the podcast on Apple Podcasts or Spotify
And the third recommendation but not less important is to watch the keynote from the past GTC 2023 conference made by Jensen.
It’s packed with information, announcements, strategic alliances, and more. If you are working in the AI field, you need to watch this keynote. Seriously. Even if you are not a prospective employee of NVIDIA.
Which role?
If you ask me about it, I would pick a role inside the NeMo LLM Service.
There are two interesting open roles there:
Why inside this service?
It’s very simple: this will become in a high-demand service for NVIDIA, and if you are part of this foundational team, this could be a career catapulting movement for you.
What do you need to know?
NVIDIA Picasso, a Cloud-Based Generative AI Service for Creating Images, Videos, and 3D Applications
If you have the chance, do this lab called: Train a Large-Scale NLP Model with NeMo Megatron
Watch this talk from Nirmalya De (Principal Product Manager- Conversational AI and Deep Learning at NVIDIA) called Efficient At-Scale Training and Deployment of Large Language Models
Getting a role inside NVIDIA won’t be easy but it’s not impossible if you put the effort into it.
I let you here some articles to prepare better for it:
Land Your Dream Job at NVIDIA, from Study Data Science
Good luck with your job application
Job Search Resources of the Week
✅ Zach Wilson on what makes a great data engineer: A conversation with Benjamin Wagner on the Firebolt Data Engineering Show. Listen on Spotify or Apple Podcasts
The next cohort of my Career Management course is now open for enrollment. I have designed this course to pack a massive amount of content very efficiently in just 2 days (4 hours each on Saturday & Sunday, plus 2-3 total hours of optional Q&A sessions).
https://
— Shreyas Doshi (@shreyas)
Jan 29, 2023
📜 Jean Kang shared on LinkedIn a lot of great tips about how to better prepare your resume for a Product Management/Program Management role.
BTW, if you are trying to get a job in those roles, definitely you must subscribe to her newsletter called “Path to PM”.
🌴 According to Marina Aisa, Apple is hiring front-end/full-stack engineers in San Diego and Barcelona
😬 Jordan Mazer (from a16z Games) shared a lot of practical tips about how to handle job offers rejections
Ben’s Bites
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Openly’s Work in Sports
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Interesting reads of the week
📉 How we reduced a 6-hour runtime in Alteryx to 9 minutes with dbt and Snowflake, by Arthur Marcon, Lucas Bergo Dias, and Christian van Bellen from Indicium Tech
📈 Scaling Databases at Activision, by Greg Smith and Vladimir Kovacik from Demonware
🤖 A very interesting perspective about what Machine Learning innovation actually means by Damien Benveniste
Final words
Thanks a lot for reading my stuff, and if you have any feedback about this new format, let me know.
Marcos out.
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