Senior Machine Learning Engineer, Recommendations

Responsibilities

• 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
• 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.

Qualifications

• Experience with translating state-of-the-art ML research into production systems
• Strong analytical and problem-solving skills
• Ability to work independently and as part of a team
• Passion for using data to solve complex business problems

Skills

• Machine Learning
• Data Science
• Deep Learning
• Python
• TensorFlow
• PyTorch

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 with company match to help save for your future
• 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

Pay

• The expected base pay range for this position in the San Francisco area is $162,800 - $203,500, not inclusive of potential equity offering, bonus or benefits.

Schedule

• This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays.
• Hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year.