Careers in AI and Engineering: Current Challenges, Opportunities, and Lessons Learned
This is a recap of the very insightful panel discussion co-hosted by WAI- San Francisco and Cadran Cowansage from Elpha on June 17, 2020. The discussions centered around a great bunch of questions that let us take a peek into the lives of these incredible Engineers with useful advice for womxn working to break into AI. Let’s get to know our panelists a little more before we dive into the discussion! First, a brief info about the two organizations that made this possible.
About Elpha:
Elpha is the place where women in tech talk candidly online. We’re a private community where members come for personal and professional development, to find jobs, and make friends. We are software engineers, founders, women in sales, VC, product, design, marketing, and more.
About Women in AI:
Women in AI (WAI) is a nonprofit do-tank working towards gender-inclusive AI that benefits global society. Our mission is to increase female representation and participation in AI. We are a community-driven initiative bringing empowerment, knowledge, and active collaboration via education, research, events, and blogging.
About the panelists:
Pujaa Rajan is a Deep Learning Engineer at Node.io. She’s also the USA Ambassador and founder of the SF Chapter for Women in AI. Previously, she worked at BlackRock, the world’s largest asset manager, Deutsche Bank, and Hudl. Having been involved in Natural Language Processing since her undergraduate years, she is very passionate about the field. Her interests lie in word embedding and model interpretability.
Sonia Joseph is currently a machine learning engineer in the Bay Area and also collaborates with FOR.ai, a multi-disciplinary research group. She studied computer science, computational neuroscience, and literature at Princeton, and wrote her thesis on natural language processing models for semantic representation in the human brain. She previously held positions at the Princeton Neuroscience Institute, the Harvard Data Science Initiative, Ruane, Cuniff, and Goldfarb.
Nikhila is a Research Engineer working on Computer Vision at Facebook AI research. She was the lead engineer on the PyTorch3D project (github.com/facebookresearch/pytorch3d), a library of reusable components for deep learning with 3D data. She is passionate about applying technology and AI to solve social problems.
Here are snippets of the conversation among our panelists:
What is your day-to-day work like?
Pujaa: As a Deep-Learning Engineer, time spent on models is a lot lower than you think, and a lot of time is spent on code that makes your model scalable. It is more software engineering than machine learning that I do.
Sonia: I spend a lot of time reading papers and implementing it and improvising to tweak existing code. One of my less likable parts about work is the long hours I sometimes spend fixing bugs.
Nikhila: I am a research engineer at Facebook. That entails writing code for pytorch3D, responding to GitHub comments, and working with internal contributors. Something that used to be challenging, which I find fun now, is writing custom backward propagation code while building neural network models from scratch. It’s pretty mathy since you have to calculate gradients manually. Over time, my role has seen an inclination towards managing projects from research.
How do you think people trying to break into a new industry approach job search, especially during uncertain times like now?
Pujaa: AI is vast. Pick an area that interests you, such as Natural Language Processing, and start there. Read a lot about it, connect with people in the field. Once you are confident in that area, you can expand your knowledge to other fields of interest. Once you know what you like, you can look into job opportunities related to it.
Sonia: Working on personal projects is a great way to gain hands-on experience in the field of your interest. You want to show not tell people that you can solve interesting problems. Along with that, networking with people is also essential. Being active in your community will eventually help you find the right people and opportunities.
Nikhila: Going off of what Sonia said, show your contribution to the community- for example, writing open-source code and publishing it on Github. If you show that you are active, people will start noticing you and will take an interest in your work.
Research shows that womxn are paid less compared to their male counterparts. What do you think are the reasons for this, and how do we solve this issue?
The collective answer was that along with discrimination in the industry, one of the main reasons womxn make less money is because we undervalue ourselves. Our salary expectations seem to be lower compared to our male peers. It is vital to research the range offered in the industry. If there is not enough data out there, it is okay to ask someone in the position of your interest. One trick that you can use is to ask someone you know through email rather than in person since it makes the discussion less awkward, and the worst that could happen is, they wouldn’t wish to disclose it, and that’s fine!
Several other topics were discussed during the event, and Careers in AI and Engineering turned out to be a vastly enriching discussion keeping the audience engaged through and through. Although we were not able to answer all questions, WAI has more exciting events coming up, where we hope to interact with everyone again!
Thank you to our panelists for joining us — Pujaa Rajan, Nikhila Ravi, and Sonia Joseph, along with Jeanine Jue, one of the Women in AI San Francisco Leads. Shout out to Ganna Tymko for leading the discussion!
Check out our upcoming events at WAI — Eventbrite, and follow us on social media: LinkedIn, Twitter.
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Sowmya Parthiban is an intern with the Women in AI, San Francisco chapter. She is a new grad from the University of California, San Diego with a specialization in Machine Learning under the Cognitive Science department.
