Machine Learning Engineer Ii, Pricing

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

Machine Learning Engineer II focused on Dynamic Supply Pricing (DSP) at Uber, developing models, algorithms, and large-scale distributed systems for real-time driver pricing. The role involves designing, developing, and productionizing end-to-end ML solutions, including deep learning, causal modeling, and reinforcement learning, for a high-volume marketplace serving millions of drivers.

What you'd actually do

  1. Design, develop, and productionize end-to-end ML solutions for large-scale distributed systems serving billions of trips
  2. Develop novel pricing approaches for online marketplaces combining machine learning, algorithmic game theory, and optimization to provide earnings opportunities for millions of drivers
  3. Partner with senior engineers to plan the scope and execution of projects and mentor junior team members on design and implementation
  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

  • Python
  • Scala
  • Java
  • Go
  • Spark
  • Ray
  • Flink
  • microservices architectures
  • MLOps
  • DNNs
  • multi-task models
  • transformers
  • LP
  • convex optimization

Nice to have

  • reinforcement learning
  • causal machine learning
  • pricing algorithms for multi-sided real-time marketplaces
  • strategic agent behavior

What the JD emphasized

  • large-scale production environments
  • large-scale distributed systems
  • real-time processing
  • large-scale data systems
  • ML solutions at scale
  • online serving
  • multi-sided real-time marketplaces

Other signals

  • real-time multi-objective optimizations
  • advanced ML models and pricing algorithms
  • large-scale distributed systems