At Lyft, community is what we are and it’s what we do. It’s what makes us different. To create the best ride for all, we start in our own community by creating an open, inclusive, and diverse organization where all team members are recognized for what they bring.
With over 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 looking to building the next-generation ML platform for low-cost, ultra-immersive transportation to improve people’s lives using modern ML using peta-byte 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.
Interns work side-by-side with top engineers in the industry while having autonomy from the get-go. They contribute to user-facing products and can see their work go live quickly. Lyft fosters a collaborative environment in the office, so there's always a sharp mind eager to hear about your next idea. If you are a student with experience in machine learning workflows, passionate about solving challenging problems using data and working in a dynamic, creative, and collaborative environment, this opportunity is for you.
- Design, build, train and test Machine Learning models
- Write production-level code to convert your ML models into working pipelines
- Partner with Product Managers, Data Scientists, and fellow ML Engineers to frame Machine Learning problems within the business context
- Analyze experimental and observational data, communicate findings, and promote launch decisions
- Participate in code reviews to ensure code quality and distribute knowledge
- Machine Learning, Deep Neural Networks; applying ML and CNN/DNN techniques to handle different tasks related to Lyft.
- Build machine learning applications using a broad range of tools such as decision trees, Hidden Markov Models, deep neural networks, etc.
- Currently in the process of obtaining a PhD degree in Computer Science or a related technical field
- Experience with research communities, including having published papers (being listed as author) at conferences (e.g. NeuraIPS, ICML, KDD, ICLR, etc).
- Deep knowledge of ML libraries like Tensorflow, PyTorch, Keras, MXNet, Caffe2, scikit-learn, etc
- Proven ability to 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 and producing high-quality code
- Demonstrated oral and written interpersonal skills
- Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment
- Great medical, dental, and vision insurance options
- 401(k) plan to help save for your future
- Monthly commuter subsidy to cover your transit to work
- Monthly cell phone reimbursement
- 20% off all Lyft rides
Lyft is an Equal Employment Opportunity employer that proudly pursues and hires a diverse workforce. Lyft does not make hiring or employment decisions on the basis of race, color, religion or religious belief, ethnic or national origin, nationality, sex, gender, gender-identity, sexual orientation, disability, age, military or veteran status, or any other basis protected by applicable local, state, or federal laws or prohibited by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. Pursuant to the San Francisco Fair Chance Ordinance and other similar state laws and local ordinances, and its internal policy, Lyft will also consider for employment qualified applicants with arrest and conviction records.