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Machine Learning Jobs at Lyft
15 open positions · Updated 1 day ago
15 Machine Learning roles across 1 company, most in AI/ML; typical advertised salary $140k
Who is hiring (1 companies)
Role types
Work arrangement: 15 hybrid
Advertised salaries: p25 $123.1k · median $140k · p75 $148k (from 13 disclosed annual salaries, USD)
Counts are open roles Joblaze currently tracks on company career pages for this exact skill/location; salaries are advertised minimums, annual, converted to USD.
Showing 15 of 15 positions
Search with filters →Own the vision and roadmap for base pricing at Lyft, driving pricing strategy and optimization in a hybrid work environment.
Lead the design and operation of production systems for real-time forecasting and optimization at Lyft.
Own the vision and roadmap for Lyft's base pricing strategy, optimizing pricing systems for a rapidly growing marketplace.
Lead the Rider Recommendations team at Lyft, focusing on AI and ML to enhance user experience in the Rider App.
Join Lyft as a Data Scientist to develop pricing algorithms and enhance rider engagement in a collaborative environment.
Influence product roadmaps through analytics and financial modeling in a hybrid role at Lyft.
Join Lyft as a Data Scientist to collaborate with engineers and product managers in solving complex business problems using data.
Join Lyft as an ML Software Engineer to enhance routing systems for millions of daily users in a collaborative environment.
Join Lyft as a Senior Machine Learning Engineer to lead the development of advanced AI systems for ride-sharing.
Join Lyft as a PhD Machine Learning Software Engineer Intern to tackle open research problems impacting millions of riders.
Join Lyft as a Data Scientist to develop dynamic pricing models and collaborate with cross-functional teams to enhance rider and driver experiences.
Join Lyft as an Applied Scientist Intern to develop AI-driven user simulation methods for rider behavior analysis.
Join Lyft as a Data Scientist on the Mapping team to enhance routing algorithms and improve travel time estimations.