2 months ago
Base Salary
$141k - $176k/yr
Responsibilities
- Design, build, and deploy machine learning models for real-time applications.
- Translate state-of-the-art machine learning research into production-ready solutions.
- Develop feature pipelines, model training workflows, and model-serving infrastructure using Lyft’s ML platform.
- Evaluate ML system performance against business KPIs, run experiments, and improve models continuously.
- Collaborate with ML engineers, product managers, data scientists, and software engineers on business-aligned ML initiatives.
- Use data-driven insights to refine ML strategies and solutions.
- Write production-quality code and participate in code reviews.
Requirements
- Bachelor’s or master’s degree in Computer Science or a related field.
- At least 2 years of experience in machine learning modeling or related fields.
- Experience with deep learning technologies for recommendation systems, including TensorFlow, PyTorch, or similar frameworks.
- Understanding of hypothesis testing, regression analysis, and machine learning performance metrics.
- Experience translating state-of-the-art ML research into production systems.
- Proficiency in Python, Golang, or another programming language.
- Ability to solve ambiguous problems and deliver solutions at scale.
- Strong communication and interpersonal collaboration skills.
Benefits
- Medical, dental, and vision insurance options with additional programs for enrolled employees.
- Mental health, family building, child care, and pet benefits.
- 401(k) plan with company match.
- Paid holidays and paid time off, with 18 weeks of paid parental leave.
- 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 flexibility to work remotely from anywhere for up to four weeks per year.
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.