Lyft · 10 hours ago
ML Software Engineer, Integrity
New York, NY
Full-time
Hybrid
Mid Level
$141K/yr - $176K/yr
3+ years expLyft is a company dedicated to serving and connecting people through innovative solutions. They are seeking a Machine Learning Engineer to develop and launch algorithms that enhance fraud detection and prevention while contributing to the Integrity team's mission of ensuring trust and safety on the platform.
AppsMobile AppsRide SharingSoftwareTaxi ServiceTransportation
Responsibilities
Develop & Lead ML Project Initiatives for Integrity, Identity and Pay: Partner with Engineers, Data Scientists, Product Managers, and Business Partners across the organization to apply machine learning for business and user impact, specifically in areas such as (supervised) fraud risk scoring, (unsupervised) anomaly detection and other applications. Drive the end-to-end lifecycle of ML projects within the Integrity domain
Drive ML Engineering Excellence: Write production-quality code to deploy and scale machine learning models. Lead investments in architecture, observability, performance, platforms, shared libraries, and tools that support robust and efficient ML operations within the Integrity team
Collaborate Cross-functionally on ML Solutions: Drive effective collaboration with cross-functional partners, including other engineering teams (e.g., Driver, Mapping, Security, Mobile Infra for signal integration), data scientists, product managers, and business partners, to define and implement comprehensive ML solutions for integrity challenges
Mentor Junior Engineers in ML: Provide technical guidance and mentorship to junior engineers, support their onboarding processes, and actively participate in hiring efforts, particularly for candidates interested in machine learning and fraud prevention
Lead Core 2026 ML Initiatives for Risk Management: Agentic AI & KarmaAI Workflows: This supports the 'Agentic workflows to scale human workloads' and the broader Karma AI (kAI) goal of an end-to-end fraud fighting loop
Risk Score & Model Lifecycle: Lead the retraining of the foundational fraud risk score model and the strategic sunsetting of legacy chargeback/debt models, ensuring adherence to RTB platform health standards for ML model lifecycle management
Driver Fraud Model Development: Drive the development and deployment of the Location Spoofing ML model, including ingestion of map matching results and advanced feature sets
Advance Foundational Signals: Behavioral Fingerprinting: Investigate and build proof-of-concept models for Behavior Fingerprinting using client signals and sequence modeling, with an early use case in signup behavior to target card testing
Data-Driven Problem Solving: Exhibit a strong passion for solving complex business problems using large-scale data, specifically focusing on identifying, analyzing, and mitigating diverse fraud vectors
Drive ML Engineering Excellence (Enhance Platform RTB): ML Infrastructure & MLOps: Demonstrate hands-on experience with robust ML infrastructure components, including 1-click deployment systems and auto-retraining pipelines. This supports the migration of ML pipelines to the latest MLP platforms and ensures high Platform Health for all maintained models
Impact Evaluation: Rigorously evaluate the performance of deployed ML models against critical business metrics (PMM, fraud loss rate) to ensure direct alignment with Integrity's strategic objectives to Reduce fraud and abuse and Strengthen trust
Qualification
Required
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
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
Company
Lyft
Lyft is a leading ride-hailing service offering car rentals, bike, and scooter-sharing through its mobile app for convenient transportation.
5001-10000 employees
H1B Sponsorship
Lyft has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (137)
2024 (100)
2023 (132)
2022 (287)
2021 (266)
2020 (281)
Funding
Current Stage
Public CompanyTotal Funding
$5.76BKey Investors
FidelityMagna InternationalCapitalG
2025-09-03Post Ipo Debt· $450M
2024-02-21Post Ipo Debt· $400M
2021-02-01Post Ipo Equity
Leadership Team
David Risher
Chief Executive Officer
Erin Brewer
Chief Financial Officer
Recent News
The Orlando Sentinel
2026-01-11
UK Investor Magazine
2026-01-11
Company data provided by crunchbase