Machine Learning Engineer II, Pricing Job at Uber in san francisco

About The Role

Uber's Marketplace is at the heart of Uber's business and the Dynamic Supply Pricing (DSP) team develops the models, algorithms, signals, and large-scale distributed systems that power real-time driver pricing for billions of rides. Engineers on the team work on cutting-edge marketplace ML problems and real-time multi-objective optimizations serving 1M+ predictions/second. They regularly present large opportunities to executive stakeholders and receive mentorship from senior engineers, enabling fast-tracked career growth and exposure to experienced technical leaders.

We are looking for exceptional ML engineers with a track record of extraordinary impact and a passion for building large-scale systems that optimize multi-sided real-time marketplaces. You will lead the design, development, and productionization of advanced ML models and pricing algorithms, covering deep learning, causal modeling, and reinforcement learning. You will work with engineers, product managers, and scientists to set the team's technical direction and solve challenging business problems to provide earnings opportunities for millions of drivers worldwide.

What You Will Do

• Design, develop, and productionize end-to-end ML solutions for large-scale distributed systems serving billions of trips
• Develop novel pricing approaches for online marketplaces combining machine learning, algorithmic game theory, and optimization to provide earnings opportunities for millions of drivers
• Partner with senior engineers to plan scope and execution of projects and mentor junior team members on design and implementation
• Collaborate with a team of engineers, product managers, and scientists to design and deliver high-impact technical solutions to complex business problems

Basic Qualifications

• Ph.D., M.S. or Bachelor's degree in Computer Science, Machine Learning, Operations Research, or equivalent technical background with demonstrated impact
• 2+ years of experience in developing and deploying machine learning models and optimization algorithms in large-scale production environments
• Proficiency in programming languages such as Python, Scala, Java, or Go
• Experience with large-scale data systems (e.g., Spark, Ray), real-time processing (e.g., Flink), and microservices architectures
• Experience in development, training, productionization and monitoring of ML solutions at scale, including offline pipelines to online serving and MLOps
• Familiarity with modern ML algorithms (e.g., DNNs, multi-task models, transformers) and mathematical optimization (e.g., LP, convex optimization) with a track record of deepening expertise

Preferred Qualifications

• Ability to translate ambiguous business problems into technical solutions in a structured way
• Strong communication skills, including documentation and design discussions
• Experience developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavior
• Experience in reinforcement learning and causal machine learning

Compensation and Benefits

Salary ranges vary by location and are listed in job postings. All full-time employees are eligible for benefits, including a bonus program, potential equity awards, and a 401(k) plan. More details can be found at the employer benefits page.

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