Senior ML Platform Engineer - AD/ADAS

Sourced from feeny.ai

Woven by Toyota is seeking a Senior ML Platform Engineer to build and scale the machine learning platform powering autonomous driving and advanced driver assist (AD/ADAS) systems. You will design tooling, pipelines, and infrastructure that let ML teams iterate efficiently on perception, prediction, and planning models shipped to millions of Toyota vehicles. The role sits at the intersection of AI, robotics, and large-scale data engineering in a hybrid Palo Alto workspace.

• Design, build, and optimize ML platform systems and tools for perception, prediction, and planner development
• Develop user-friendly tooling, frameworks, and libraries supporting ML modeling, metrics tracking, and failure-mode introspection
• Build and maintain efficient dataset generation, cloud training, and evaluation pipelines
• Collaborate with ML and ML Platform engineers to drive rapid incremental improvements
• Optimize processes, tooling, and infrastructure to accelerate ML engineering and contribute to long-term strategy
• Work in a high-velocity environment using agile development practices

• BSc/BEng (MS/PhD a plus) in Machine Learning, Computer Science, Robotics, or related quantitative field, or equivalent experience
• 5+ years of experience with data structures, algorithms, design patterns, and software engineering best practices
• 2+ years with UNIX-based systems, Python, and PyTorch/TensorFlow
• 2+ years across the full MLOps cycle: data cleansing, curation, preprocessing, distributed training, evaluation, deployment, and inference optimization on cloud and edge
• Experience with Docker and CI systems such as GitHub Actions
• Business-level English proficiency for technical documentation

• 2+ years with Apache Spark, Airflow, Flyte, Flink, Ray, or similar ML pipeline technologies
• 2+ years with Rust and/or C++ and a modern build system (preferably Bazel), plus systems-level debugging
• Experience with SIMD/SIMT parallelism, GPU programming, and multithreading
• Experience with Terraform, AWS, observability, and Kubernetes in production
• Experience with BigQuery, Snowflake, or Redshift in production
• Experience optimizing deep-learning models for specific hardware targets
• Experience in self-driving, robotics, computer vision, or motion planning
• Business-level Japanese proficiency