Backed by a16z and Founders Fund.
About the role
As a PhD Machine Learning Engineer Intern on our Applied AI team, you'll take on an open research problem tied to product experiences used by millions of riders. Working closely with a Staff ML Engineer mentor, you'll scope the problem, develop and evaluate new methods on real data, and take the work far enough that it can be shared with the research community, with the goal of a paper submission to a top ML venue. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- A track record of ML research, shown through publications, preprints, or substantial research projects
- Strong foundation in reinforcement learning and sequential decision making, especially problems with delayed or long-horizon rewards
- Solid grounding in both causal inference and counterfactual evaluation
- Good understanding of ML libraries like PyTorch, TensorFlow, or JAX
- Strong programming skills in Python or a similar language
- Proven ability to effectively turn research ML papers into working code
More about this role
At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.
With over half a billion rides and counting, Lyft is solving hard problems in a flourishing domain with a lot of data and creative solutions in Marketplace, Mapping, Fraud, Growth and beyond. We're actively building the next-generation Machine Learning (ML) platform for low-cost, ultra-immersive transportation to improve people’s lives using modern ML with petabyte-scale data. Our Machine Learning Engineers are excited to work on these challenging problems and redefine solutions to directly impact various aspects of Lyft's primary business.
As a PhD Machine Learning Engineer Intern on our Applied AI team, you'll take on an open research problem tied to product experiences used by millions of riders. Working closely with a Staff ML Engineer mentor, you'll scope the problem, develop and evaluate new methods on real data, and take the work far enough that it can be shared with the research community, with the goal of a paper submission to a top ML venue.
If you are a PhD student who enjoys turning open-ended research...
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