Senior Machine Learning Engineer, Recommendations at Lyft

<p>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.</p> <p>With a billion rides per year and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Rider, Marketplace, Growth, and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building a next-generation platform for low-cost, ultra-immersive transportation to improve people's lives warrants modern ML utilizing peta-byte scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business.</p> <p>If you are a critical thinker with experience in machine learning workflows and LLMs, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you.</p> <p>We are seeking a <strong>Senior Machine Learning Engineer</strong> to join the Rider Applied AI team and lead the design, development, and deployment of state-of-the-art machine learning and artificial intelligence systems. This role requires a strategic thinker who can balance high-level system architecture with hands-on technical implementation. You will collaborate across teams to shape the future of ride-sharing by leveraging AI, Machine learning and Data science.</p> <h2><strong>Responsibilities:</strong></h2> <ul> <li><strong>Model Development & Research:</strong> Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions.</li> <li><strong>System Design:</strong> Architect scalable, reliable ML pipelines that integrate seamlessly with existing backend systems.</li> <li><strong>Innovation & Applied Research:</strong> Stay ahead of the curve by exploring emerging algorithms, technologies (such as LLMs and LLM-based applications), and frameworks — critically evaluating new research and identifying high-impact use cases across business areas.</li> <li><strong>Collaboration:</strong> Partner with ML engineers, product managers, data scientists, and software engineers to align ML initiatives with business goals.</li> <li><strong>Data-Driven Decision Making:</strong> Leverage data-driven insights to inform and refine ML strategies and solutions.</li> <li><strong>Mentorship & Technical Leadership:</strong> Provide technical direction, mentor Junior engineers, and foster a culture of learning and collaboration.</li> <li><strong>Code Quality:</strong> Write production-level code and participate in code reviews to ensure quality and share knowledge across the team.</li> </ul> <h2><strong>Experience:</strong></h2> <ul> <li> <ul> <li>M.S. or Ph.D. in Computer Science or related technical field</li> <li>5+ years (or Ph.D. with 3+ years) of experience in machine learning modelling or related fields</li> <li>Experience with deep learning technologies for recommendation systems, including TensorFlow, PyTorch, or similar frameworks</li> <li>Understanding of statistical concepts such as hypothesis testing, regression analysis, and performance evaluation metrics for machine learning</li> <li>Experience with translating state-of-the-art ML research into production systems</li> <li>Proficiency in Python, Golang, or other programming language</li> <li>Proven ability to tackle ambiguous problems and deliver solutions at scale.</li> <li>Strong communication and interpersonal skills for effective cross-functional collaboration.</li> </ul> </li> </ul> <h2><strong>Benefits:</strong><strong><br></strong></h2> <ul> <li>Great medical, dental, and vision insurance options with additional programs available when enrolled</li> <li>Mental health benefits</li> <li>Family building benefits</li> <li>Child care and pet benefits</li> <li>401(k) plan with company match to help save for your future</li> <li>In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off</li> <li>18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible</li> <li>Subsidized commuter benefits</

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