Staff Machine Learning Engineer

Uber Uber · Consumer · San Francisco, CA · Engineering

Staff Machine Learning Engineer at Uber Marketplace focused on optimizing rider & driver matching using optimization, machine learning, and causal inference. The role involves building scalable ML libraries and systems, improving the ML Platform ecosystem, and collaborating with the ML community. Requires PhD or equivalent, 5+ years of experience, and proficiency in modern ML algorithms and frameworks.

What you'd actually do

  1. Build elastic, scalable, and fault-tolerant distributed machine learning libraries and systems used to power machine learning development productivity across Uber.
  2. Work closely with engineers in the broader Uber ML/AI Platform Team (Michelangelo) to improve the broader ML Platform ecosystem for our users.
  3. Work closely with Uber's ML community (with ML Engineers, Data Scientists, and Researchers) to scope and build new abstractions for scalable machine learning.

Skills

Required

  • PhD or equivalent in Computer Science, Engineering, Mathematics or related field
  • Programming language (e.g. C, C++, Java, Python, or Go)
  • 5+ years of proven experience in the industry
  • Large-scale training using data structures and algorithms
  • Modern machine learning algorithms (e.g., tree-based techniques, supervised, deep, or probabilistic learning)
  • Machine Learning Software such as Tensorflow/Pytorch, Caffe, Scikit-Learn, or Spark MLLib

Nice to have

  • Causal ML
  • Reinforcement learning
  • Contextual bandit models
  • Personalization and ranking experience
  • 8-10+ years of proven experience in the industry

What the JD emphasized

  • production code
  • scalable systems
  • scalable machine learning

Other signals

  • optimize rider & driver matching
  • develop highly reliable and scalable platforms
  • writing production code
  • converting ideas to scalable systems