Senior Software Engineer, ML Infrastructure, Predictive Planner

Waymo; San Francisco (CA); On-site; USD 204,000 - 259,000; Full time

Job summary

An innovative technology firm is seeking a talented Machine Learning Engineer to join their mission of revolutionizing mobility through autonomous driving. This role involves collaborating with data scientists and engineers to deploy cutting-edge ML models into production while ensuring system reliability amidst rapid development. You will develop and maintain CI/CD pipelines, implement best practices for model governance, and troubleshoot deployment issues. With your expertise in Python, C++, and ML tools, you will contribute to shaping the future of transportation. If you're passionate about machine learning and eager to make an impact, this opportunity is perfect for you!

Benefits

Discretionary Bonuses

Equity

Comprehensive Company Benefits

Qualifications

• 5+ years of experience with high-scale distributed or ML inference systems.
• Proficiency in Python and C++ coding and testing.

Responsibilities

• Collaborate with teams to deploy ML models into production.
• Develop CI/CD pipelines for automating model training and deployment.

Skills

Python

C++

Machine Learning

CI/CD

DevOps

Large Language Models

Reinforcement Learning

Vision Understanding

Education

B.S. in Computer Science

Equivalent Experience

Tools

GCP

AWS

Kubernetes

Jenkins

GCS/S3

tf.serving

Torchserve

Kubeflow

Sagemaker

Vertex AI Pipelines

Job description

Waymo is an autonomous driving technology company with the mission to be the most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—the world's most experienced driver—to improve access to mobility while saving lives. The Waymo Driver powers Waymo One, a fully autonomous ride-hailing service, and is adaptable to various vehicle platforms and use cases. It has completed over one million rider trips and driven tens of millions of miles on public roads across 13+ U.S. states, supported by extensive simulation.

The Waymo Driver is powered by machine learning, and with recent advances, we aim to tackle the next frontier of planning problems. Our work involves cutting-edge ML topics, including Large Language Models (LLMs), Reinforcement Learning (RL), and vision understanding. In this role, you will ensure our systems remain reliable amidst rapid, experimental development.

You will:

• Collaborate with data scientists, engineers, and stakeholders to deploy ML models into production.
• Develop and maintain CI/CD pipelines for automating data generation, model training, testing, and deployment.
• Implement best practices for model versioning, monitoring, and governance.
• Troubleshoot and resolve deployment and performance issues.
• Stay current with emerging ML Ops and DevOps technologies and trends.
• Apply best practices from the Alphabet ML stack (e.g., TF, JAX, Flax, Beam).

You have:

• B.S. in Computer Science, Math, or equivalent experience.
• 5+ years of experience building and maintaining high-scale distributed or ML inference systems.
• Proficiency in Python and C++ coding and testing.
• Experience with large-scale fleet management, testing, and deployment tools like GCP, AWS, Kubernetes, Jenkins, GCS/S3.
• Familiarity with ML tools such as tf.serving, Torchserve, Kubeflow, Sagemaker, Vertex AI Pipelines.
• Understanding of ML fundamentals and experience with frameworks like JAX, PyTorch, or TensorFlow.

Preferred:

• Experience deploying ML models for computer vision, NLP, or recommendation systems.

The expected base salary range for this full-time position across US locations is $204,000—$259,000 USD. Actual salary depends on location, experience, training, and skills. Additional benefits include discretionary bonuses, equity, and comprehensive company benefits.