Senior Machine Learning Engineer, Recommendations
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Role details
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Job description
- Model Development & Research: Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions.
- System Design: Architect scalable, reliable ML pipelines that integrate seamlessly with existing backend systems.
- Innovation & Applied Research: 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.
- Collaboration: Partner with ML engineers, product managers, data scientists, and software engineers to align ML initiatives with business goals.
- Data-Driven Decision Making: Leverage data-driven insights to inform and refine ML strategies and solutions.
- Mentorship & Technical Leadership: Provide technical direction, mentor Junior engineers, and foster a culture of learning and collaboration.
- Code Quality: Write production-level code and participate in code reviews to ensure quality and share knowledge across the team.
Requirements
- M.S. or Ph.D. in Computer Science or related technical field
- 5+ years (or Ph.D. with 3+ years) of experience in machine learning modelling or related fields
- Experience with deep learning technologies for recommendation systems, including TensorFlow, PyTorch, or similar frameworks
- Understanding of statistical concepts such as hypothesis testing, regression analysis, and performance evaluation metrics for machine learning
- Experience with translating state-of-the-art ML research into production systems
- Proficiency in Python, Golang, or other programming language
- Proven ability to tackle ambiguous problems and deliver solutions at scale.
- Strong communication and interpersonal skills for effective cross-functional collaboration.
Benefits & conditions
- 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 with company match 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
- Monthly Lyft credits and complimentary Lyft Pink membership
About the company
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.
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.
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.
We are seeking a Senior Machine Learning Engineer 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.
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