Software Engineer, Model Lifecycle

Software Engineer Model Lifecycle 4592 On Site Kirkland Washington Software Engineering Full-Time

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Waymo is an autonomous driving technology company with the mission to be the worlds most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The Worlds Most Experienced Driver-to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymos fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15 U.S. states.

The core challenge within Model Lifecycle is accelerating Waymos ML development cycle. As we scale to new cities and vehicle platforms, our data volume is exploding and our models are becoming more complex, handling more and more tasks. This team is critical to controlling that complexity.

In this hybrid role, you will report to an engineering manager.

Design, build, and maintain scalable data pipelines to process many petabytes of complex sensor data, making it ready for efficient model training and evaluation.

Develop infrastructure to produce reliable, high-quality datasets for a wide range of ML models from real-time on-car models to large-scale offboard foundation models.

Build towards an automated unified data flywheel-a datagen and ingestion solution that seamlessly connects data curation to model training.

Develop infrastructure for Perception-wide model training and release-ready packaging, ensuring the model development lifecycle is robust, efficient, and reproducible.

Maintain and support critical data generation infrastructure and data refreshes for the Perception team.

Automate data quality and validation checks to ensure the integrity, consistency, and trustworthiness of our datasets as we scale to new cities and vehicle platforms.

Collaborate closely with ML engineers, research scientists, and core infrastructure teams to understand user needs and deliver impactful ML workflows.

Requirements:

• Outstanding programming skills in C or Python
• Experience in ML data engineering, including data pipelines, data curation, data balancing, etc.
• Experience with the ML development lifecycle, including data engineering, model training, model evaluation, and model deployment
• BSMS and 5 years of industry experience or PhD, 2 years of industry experience

Preferred Qualifications:

• Experience in working in cross-functional settings to support data users and collaborating with infrastructure stakeholders
• Customer-oriented mindset
• Hands-on experience in building large-scale data processing or retrieval systems and pipelines (Apache Spark, Apache Beam, Google Cloud Dataflow, AWS Data Pipeline, Faiss, ScaNN, etc.)
• Experience building automated ML pipelines-data pipelines, continuous model training, evaluation pipelines, etc.

Salary Range:

The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training, education, and skill level. Your recruiter can share more about the specific salary range for the role, location, or if the role can be performed remote, the specific salary range for your preferred location during the hiring process.

Benefits:

Waymo employees are also eligible to participate in Waymos discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.