3 months ago
Base Salary
$141k - $176k/yr
Responsibilities
- Perform data analysis and build proof-of-concept solutions to compare machine-learning and non-machine-learning approaches.
- Develop statistical, machine-learning, or optimization models.
- Write scalable, production-quality code capable of serving millions of requests per day.
- Write well-tested, readable, maintainable code and participate in code and design reviews.
- Participate in production on-call support and incident triage.
Requirements
- Bachelor’s, master’s, or doctoral degree in computer science, a quantitative field, or equivalent related work experience.
- At least 3 years of machine-learning experience.
- Experience with machine-learning workflows and writing reliable, production-quality code.
- Ability to make tradeoffs among model accuracy, productization complexity, and runtime performance.
- Ability to work effectively in distributed teams across North American and European time zones.
- Preferred: experience with big-data processing, distributed data pipelines, Apache Airflow, and Spark.
Benefits
- Medical, dental, and vision insurance options with additional programs available when enrolled.
- Mental health, family building, child care, and pet benefits.
- 401(k) plan with company match.
- Paid holidays and paid time off; salaried employees receive discretionary PTO and hourly employees receive 15 days.
- 18 weeks of paid parental leave for biological, adoptive, and foster parents.
- Subsidized commuter benefits, monthly Lyft credits, and complimentary Lyft Pink membership.
- Hybrid schedule requiring in-office work three days per week on Mondays, Wednesdays, and Thursdays, with up to four weeks of remote work per year.
Tech Stack
Categories
About Lyft
Lyft is a NASDAQ-listed transportation marketplace that connects riders with drivers and offers bike and scooter rentals in one app. Founded in 2012 and headquartered in San Francisco, it operates across the U.S. and parts of Canada. Its revenue comes from service fees on rides and rentals, enterprise programs, and consumer subscriptions such as Lyft Pink.