ML Software Engineer, Integrity

Lyft • San Francisco, CA

6d • Hybrid

About The Position

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. Our engineering team is growing rapidly, and we are looking for a Machine Learning Engineer. As a machine learning engineer, you will be developing and launching the algorithms that power the platform’s core services. Compared to similarly-sized technology companies, the set of problems that we tackle is incredibly diverse. They cut across transportation, economics, forecasting, mapping, personalization, and adaptive control. We are hiring motivated experts in each of these fields. We’re looking for someone who is passionate about solving problems with data, building reliable ML systems, and is excited about working in a fast-paced, innovative, and collegial environment. An ML SWE in the Integrity team is a specialized role focusing on the application of machine learning to enhance fraud detection and prevention. This role operates at a leadership and system ownership level comparable to a general SWE but with a deep specialization in ML. The individual will contribute significantly to the team's engineering excellence and operational responsibilities. This role is a highly specialized engineering position that leverages deep machine learning expertise to directly impact the Integrity team's core mission: reducing fraud, ensuring trust and safety on the Lyft platform, and contributing to the development of cutting-edge AI-driven fraud-fighting platforms.

Requirements

• B.S., M.S., or Ph.D. in Computer Science or other quantitative fields or related work experience
• 3+ years of Machine Learning experience
• Passion for building impactful machine learning models leveraging expertise in one or multiple fields.
• Proficiency in Python, Golang, or other programming language
• Excellent communication skills and fluency in English
• Strong understanding of Machine Learning methodologies, including supervised learning, forecasting, recommendation systems, reinforcement learning, and multi-armed bandits

Responsibilities

• Develop & Lead ML Project Initiatives for Integrity, Identity and Pay
• Drive ML Engineering Excellence
• Collaborate Cross-functionally on ML Solutions
• Mentor Junior Engineers in ML
• Lead Core 2026 ML Initiatives for Risk Management: Agentic AI & KarmaAI Workflows
• Risk Score & Model Lifecycle
• Driver Fraud Model Development
• Advance Foundational Signals: Behavioral Fingerprinting
• Data-Driven Problem Solving
• Drive ML Engineering Excellence (Enhance Platform RTB): ML Infrastructure & MLOps
• Impact Evaluation

Benefits

• Great medical, dental, and vision insurance options with additional programs available when enrolled
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• 401(k) plan to help save for your future
• In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• Subsidized commuter benefits
• Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 1,001-5,000 employees