Machine Learning Engineer II - AV Labs

Uber

Quick summary

Work type
On-site
Location
Sunnyvale, CA
Salary
$171,000–$171,000 / yr
Posted
8 days ago

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $217k
This role $171k
$160k most similar roles pay here $273k

This role pays less than 85% of similar roles. Most pay $184,050–$249,750 — the shaded band above. At the midpoint, this role pays about $171k versus about $217k for comparable roles.

Based on 240 similar postings.

Employer

About Uber

Uber Technologies, Inc. is the world’s largest, San Francisco-based mobile technology platform facilitating on-demand ride-hailing, food delivery (Uber Eats), and freight transportation across approximately 70 countries.

Uber currently has 95 open roles on FindRole.

Listed pay typically runs $232,000–$232,000 across 76 roles with salary data.

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At a glance

TL;DR · Machine Learning Engineer II - AV Labs

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As a Machine Learning Engineer II at AV Labs in Sunnyvale, you will lead the development of advanced autonomy algorithms and models to enhance semantic understanding from driving data. Your daily tasks include creating robust algorithms for complex urban scenarios, designing scalable ML systems, optimizing datasets through sensor data processing, and collaborating with cross-functional teams to deploy machine learning techniques into production environments. The role requires proficiency in Python and Linux, along with experience using frameworks like PyTorch. Ideal candidates have a background in autonomous driving and a proven ability to implement ML models in safety-critical systems, making this an excellent opportunity for those passionate about physical AI and data-driven autonomy solutions at scale.

Skills

Python Linux PyTorch AWS Kubernetes Git CI/CD PostgreSQL Docker TensorFlow CUDA ROS Raspberry Pi C++ CVXPY

What you'll do

  • Develop algorithms to extract semantic meaning from complex urban edge cases for L4 data lake enrichment.
  • Implement scalable ML systems managing upstream sensor dependencies.
  • Optimize datasets by advancing sensor data collection, processing, and auto-labeling techniques.
  • Identify and solve complex edge cases with robust algorithmic solutions.
  • Set high technical standards for autonomy algorithms and models.

What we're looking for

  • 2+ years experience in ML/Robotics industry
  • Bachelor’s degree in Computer Science, Engineering, or related field
  • Proficiency in Python and Linux environments
  • Experience with modern AI/ML frameworks like PyTorch
  • Familiarity with C++ and high-performance computing
  • Track record of deploying ML models in safety-critical systems

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