Designs and operates public-cloud infrastructure for engineering teams, using Infrastructure as Code, governance, automation, and deployment pipelines to improve secure, reliable services.
About this role
This Staff ML Platform Engineer role sits within Woven by Toyota's AD/ADAS team, which works on autonomous driving and advanced driver-assistance technology spanning perception, prediction, and planning. The role is on the ML Platform team, working closely with machine learning engineers to accelerate and scale ML development. Responsibilities include designing, building, maintaining, and optimizing machine learning platform systems and tools that let ML engineers efficiently curate datasets, model, train, evaluate, and deploy; building easy-to-use tools, frameworks, and libraries covering modeling, performance monitoring, and failure-mode analysis; building and maintaining data curation and cloud training/evaluation pipelines; reviewing code with other ML and platform engineers; and optimizing current processes, tools, and infrastructure while contributing to long-term technical strategy. Work is agile and fast-paced, under a hybrid policy requiring three days per week in the Nihonbashi office. Requirements: a bachelor's degree in machine learning, computer science, robotics, or a related field (or equivalent experience); 10+ years of experience with data structures, algorithms, design patterns, and software engineering best practices; 4+ years with Unix-like systems, Python, and PyTorch or TensorFlow; 4+ years across the MLOps cycle from data cleansing through cloud and edge deployment; experience scaling ML training in large environments; and experience with Docker and CI systems such as GitHub Actions. Business-level English is required, including for writing software documentation.
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