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Senior ML Platform Engineer - AD/ADAS
Woven by Toyota
Senior ML Platform Engineer - AD/ADAS
This job is still taking applications, but it's been up a while.
About the job
Woven by Toyota is transforming mobility with autonomous driving, AI, and software platforms. The role focuses on building ML platforms for perception, prediction, and planning, impacting millions of vehicles with human-centric innovation.
Requirements
- 5+ years software engineering experience
- Experience with Python, PyTorch/TensorFlow
- UNIX/Linux experience
- Full MLOps cycle knowledge
Qualifications
- BSc/BEng in relevant field
- Strong problem-solving skills
- Good communication skills
- Experience in fast-paced teams
Full job description
TEAM
WHO ARE WE LOOKING FOR?
RESPONSIBILITIES
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.
MINIMUM QUALIFICATIONS
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).
NICE TO HAVES
2+ years of experience with Apache Spark, Airflow, Flyte, Flink, Ray, or similar ML pipelines technologies.
2+ years using modern systems programming languages (e.g., Rust and/or C++) and a modern build system (preferably Bazel), and systems-level debugging knowledge, in a professional environment.
Experience with SIMD/SIMT parallelism, GPU programming, multithreading.
Experience with Terraform, AWS, Observability, and Kubernetes in production.
Experience with Google Big Query, Snowflake or AWS Redshift in production.
Experience in optimizing deep-learning models towards specific hardware targets.
Experience in self-driving, robotics, computer vision, or motion planning.
Experience working in a fast-paced environment, collaborating across teams and disciplines.
Business-level proficiency in Japanese.
Your base salary is one part of your total compensation. We offer a base salary, short term and long term incentives, and a comprehensive benefits package. The total compensation offered to an employee will be dependent upon the individual's skills, experience, qualifications, location, and level.
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