Senior ML Platform Engineer, AD/ADAS

業務内容

• Design, build, maintain and optimize the ML Platform systems and tools for perception, prediction, and planner development, enabling ML engineers to iterate on dataset curation, ML modeling, training, evaluation and deployment into the AD/ADAS stack shipped in Toyota vehicles
• Develop user-friendly tooling, frameworks and libraries to support end-to-end ML engineering (model tracking, performance metrics, failure-mode introspection)
• Build and maintain efficient dataset generation, cloud training and evaluation pipelines; optimize data loading and distributed training, plus cloud/edge deployment
• Review code and collaborate with ML/ML Platform engineers to accelerate incremental improvements; contribute to long-term platform strategy
• Operate in a high-velocity, agile environment with a hybrid Tokyo office presence ( Nihonbashi) three days per week

技術スタック

必須スキル

• 5+ years in software engineering with strong data structures, algorithms, design patterns and best practices
• 2+ years UNIX-based systems (Linux), Python, and PyTorch/TensorFlow
• 2+ years full MLOps lifecycle: data cleansing/sampling/curation, preprocessing, distributed training, evaluation, deployment, inference optimization (cloud and edge)
• Docker and CI systems (GitHub Actions)
• Business-level English (technical writing)

歓迎スキル（該当する場合）

• 2+ years with Apache Spark, Airflow, Flyte, Flink, Ray or similar ML pipelines
• 2+ years with Rust and/or C++, Bazel, systems-level debugging
• SIMD/SIMT, GPU programming, multithreading
• Terraform, AWS, Observability, Kubernetes in production
• BigQuery, Snowflake, or AWS Redshift in production
• Experience in self-driving, robotics, computer vision, or motion planning
• Japanese language proficiency

キャリア成長観点

• AD/ADAS領域のMLプラットフォーム全体を担い、億単位の車両にデプロイされるモデル開発・運用を横断的に最適化する機会、モビリティの安全性・社会貢献へ直結する影響力
• データ/モデル/MLOpsのエンドツーエンドを支える tooling・パイプラインの設計・改善から長期戦略の策定まで、技術と組織の両輪で成長できる環境
• 高速な開発環境・クロスファンクショナルな協働、ハイブリッド勤務、最新ハードウェアと分散システムの最適化など、上流から運用・現場適用まで幅広いスキルを磨ける機会