Senior ML Platform Engineer – AD/ADAS

Woven Planet

Senior ML Engineer developing and optimizing machine learning infrastructure for automated driving solutions at Woven by Toyota. Collaborating with teams to scale ML technologies for millions of vehicles.

Posted 7/15/2026full-timePalo Alto • California • 🇺🇸 United StatesSenior💰 $140,000 - $230,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Machine Learning engineering, including MLOps processes, data management, and cloud deployment. Proficient in developing user-friendly tools and optimizing ML systems for high-performance applications in autonomous driving.

Highest-signal resume keywords

Machine Learning EngineeringMLOps CyclePython ProgrammingPyTorch/TensorFlowUNIX-Based Systems

ATS Keywords

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Hard Skills

Data StructuresAlgorithmsDesign PatternsSoftware Engineering Best PracticesData CleansingData SamplingData CurationPre-ProcessingDistributed TrainingInference Optimization

Soft Skills

Technical WritingCollaboration

Tools & Technologies

DockerCI SystemsGitHub ActionsCloud Platforms

Industry Keywords

Machine LearningAutonomous DrivingADASAgile DevelopmentHybrid Workspace

Tech Stack

Tools & technologies

CloudDockerLinuxPythonPyTorchTensorflowUnix

About the role

Key responsibilities & impact

Design, build, maintain, optimize and support the ML Platform’s systems and tools for perception, prediction, and planner development, allowing numerous ML engineers to effectively & efficiently iterate on dataset curation, ML modeling, training, evaluation and deployment of ML models into our functionally safe AD/ADAS stack, shipped in millions of Toyota vehicles.
Develop user-friendly tooling, frameworks and libraries to support the overall ML engineering effort, from ML modeling, to tracking performance metrics and introspecting failure modes.
Build and maintain efficient dataset generation, cloud training and evaluation pipelines.
Develop and review code with other ML and ML Platform engineers to facilitate rapid incremental improvements.
Optimize the current processes, tooling and supporting infrastructure to accelerate the overall ML engineering effort, and contribute to the long term strategy for several of our systems and products.
Work in a high-velocity environment and employ agile development practices.
Work in a hybrid workspace, with the requirement to be present in our Palo Alto (USA) office three days per week.

Requirements

What you’ll need

BSc / BEng (MS / PhD nice-to-have) in Machine Learning, Computer Science, Robotics or related quantitative fields, or equivalent industry experience.
5+ years of experience with data structures, algorithms, design patterns, and software engineering best practices.
2+ years of experience with UNIX-based systems (Linux or similar), Python, and PyTorch/Tensorflow.
2+ years of experience in the full MLOps cycle covering data cleansing, data sampling, data curation, pre-processing, efficient data loading, distributed training, testing, evaluation, deployment, inference optimization and deployment in the cloud and on edge compute platforms.
Experience with Docker and CI systems such as GitHub Actions.
Business-level proficiency in English, able to write technical documents (e.g., for software documentation).

Benefits

Comp & perks

Excellent health, wellness, dental and vision coverage
A rewarding 401k program
Flexible vacation policy
Family planning and care benefits