Staff Machine Learning Engineer - Marketplace Pricing

Uber Uber · Consumer · Sunnyvale, CA +2 · Engineering

Staff ML Engineer role focused on developing and productionizing advanced ML models and pricing algorithms for Uber's Marketplace Pricing, involving deep learning, causal modeling, and reinforcement learning in large-scale distributed systems serving billions of trips.

What you'd actually do

  1. Drive technical strategy and roadmap ownership over a 1+ year horizon and own the implementation, including platform-level architecture decisions, executive communication and alignment, technical mentorship, and cross-team technical influence
  2. Lead the design, development, and productionization of end-to-end ML solutions for large-scale distributed systems serving billions of trips
  3. Develop novel pricing approaches for online marketplaces combining machine learning, algorithmic game theory, and optimization to provide earnings opportunities for millions of drivers
  4. Work with a team of engineers, product managers, and scientists to design and deliver high-impact technical solutions to complex business problems

Skills

Required

  • Ph.D., M.S. or Bachelor's degree in Computer Science, Machine Learning, or Operations Research, or equivalent technical background with exceptional demonstrated impact
  • 6+ years experience leading the development and deployment of ML models and optimization algorithms in large-scale production environments at top-tier ML companies (e.g. 1M+ predictions/sec or 100M+ users). Track record of delivering outstanding business impact over multiple quarters
  • Proficiency in programming languages such as Python, Scala, Java, or Go
  • Proficiency with large-scale data systems (e.g. Spark, Ray), real-time processing (e.g. Flink), and microservices architectures
  • Proficiency in the development, training, productionization and monitoring of ML solutions at scale, ranging from offline pipelines to online serving and MLOps
  • Experience in developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavior
  • Deep understanding of modern ML algorithms (e.g. DNNs, multi-task models, transformers) and mathematical optimization (e.g. multi-objective, LP, convex optimization)

Nice to have

  • Experience developing multi-year technical strategies and cross-team platform architecture, and proficiency owning technical roadmap and leading complex technical projects while substantially influencing the scope and output of others
  • Track record of translating complex business problems into technical solutions and driving multi-functional projects across multiple teams
  • Excellent communication skills to lead initiatives across multiple product areas and collaborate effectively with cross-functional teams
  • Proficiency in reinforcement learning and causal machine learning

What the JD emphasized

  • 6+ years experience leading the development and deployment of ML models and optimization algorithms in large-scale production environments at top-tier ML companies (e.g. 1M+ predictions/sec or 100M+ users). Track record of delivering outstanding business impact over multiple quarters
  • Experience in developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavior
  • Deep understanding of modern ML algorithms (e.g. DNNs, multi-task models, transformers) and mathematical optimization (e.g. multi-objective, LP, convex optimization)

Other signals

  • real-time multi-objective optimizations
  • large-scale distributed systems
  • advanced ML models and pricing algorithms
  • deep learning, causal modeling, and reinforcement learning