At Lyft, our mission is to improve peoples lives with the worlds best transportation. To do this, we start with our own community by creating an open, inclusive, & diverse organization.
With over half a billion rides & counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data & creative solutions in multiple domains, including Mapping & Search. While traditional approaches to optimization & problem decomposition are sufficient to disrupt transportation, building next-generation platform for low-cost, ultra-immersive transportation to improve peoples lives warrants modern ML utilizing peta-byte scale data. We are building an in-house search engine to help our riders & drivers find the right spots & places to efficiently get to their destinations.
If you are a critical thinker with experience in machine learning workflows, passionate about solving business problems using data & working in a dynamic, creative, & collaborative environment, we are searching for you.
- Design, build, train, evaluate & test Machine Learning models, focusing on Search applications
- Write production-level code to convert your ML models into working pipelines
- Work closely with Product Managers, Data Scientists, & fellow ML Engineers to frame Machine Learning problems within the business context
- Analyze experimental & observational data, communicate findings, & facilitate launch decisions
- Participate in code reviews to ensure code quality & distribute knowledge
- B.S., M.S. or Ph.D. in Computer Science, related technical field or relevant work experience
- 3+ years of industry or research experience developing ML models
- Deep knowledge of ML libraries like scikit-learn, Tensorflow, PyTorch, Keras, MXNet, etc
- Proven ability to quickly & effectively turn research ML papers into working code
- Practical knowledge of how to build efficient end-to-end ML workflows
- Engineer at heart with a high degree of comfort in designing software systems & producing high-quality code
- Strong oral & written interpersonal skills
- Professional & stable working environment.
- The latest technology & equipment you need.
- English classes with native speakers.
- 28 calendar days for vacation & up to 10 paid days off.
- Spacious office facing National Library + opportunity to work remotely