Senior ML Engineer – Autonomous Driving & Planning Systems

Neura Market; Mountain View, Northern (CA, KY); Hybrid; USD 213,000 - 263,000; Full time

Benefits offered by this job

Annual bonus program

Equity incentive plan

Benefits program

Job summary

Waymo seeks an experienced ML professional to advance the Waymo Driver through production-grade machine learning models and planning systems. You will design, implement, and optimize ML architectures and pipelines, collaborating with researchers and engineers to deploy models on autonomous vehicle software stacks, ensuring safety and reliability.

The role emphasizes cross-functional teamwork across data, modeling, and systems, with research-driven expectations and a focus on scalable, real-world

Qualifications

• Bachelor’s degree in Computer Science, ML, Robotics, or equivalent practical experience.
• Hands-on experience with modern deep learning libraries (e.g., TensorFlow, JAX, PyTorch).
• Proficient programming skills (Python, C/C++).
• Strong analytical and problem-solving abilities.
• 4+ years of ML modeling and/or autonomous vehicles systems experience.

Responsibilities

• Tackle challenging real-world problems with ML and engineering solutions.
• Use state-of-the-art techniques to design and build ML models and deploy them in production on autonomous vehicles.
• Design and build architectures, pipelines, and evaluation systems on large data infrastructure.
• Collaborate with researchers, product owners, and engineers to deliver safe, smooth planning behavior for road users.

Skills

Python

C/C++

Deep learning

Analytical skills

Education

Bachelor's degree in CS/ML/Robotics or equiv

Tools

TensorFlow

JAX

PyTorch

Job description

Waymo seeks an experienced ML professional to advance the Waymo Driver through production-grade machine learning models and planning systems. You will design, implement, and optimize ML architectures and pipelines, collaborating with researchers and engineers to deploy models on autonomous vehicle software stacks, ensuring safety and reliability.

The role emphasizes cross-functional teamwork across data, modeling, and systems, with research-driven expectations and a focus on scalable, real-world