業務内容

• Lead design and development of advanced ML models for autonomous vehicles using deep learning, simulation, and large-scale data analysis
• Deploy scalable and efficient ML models on the autonomous vehicle platform with safety and cost considerations
• Contribute to end-to-end ML training/deployment components, from data strategy to optimization and validation
• Champion the scientific method and critical thinking to invent state-of-the-art deep learning solutions
• Collaborate across Perception, Motion Planning, Simulation, Infrastructure, and Tooling; in a hybrid setup with 3 days/week in Nihonbashi office

技術スタック

必須スキル

• MS/PhD in ML/CS/Robotics or equivalent, or 3+ years industry experience
• Python (3+ years) with major deep learning framework and software engineering practices
• C++ for integration with autonomous vehicle platform
• 3+ years in deep learning approaches (pretraining, distillation, unsupervised/supervised, multi-task, DRL)
• 3+ years in ML workflows: data sampling/curation, preprocessing, training, ablation, evaluation, deployment, inference optimization
• Strong communication skills

歓迎スキル（該当する場合）

• Published research at NeurIPS/CVPR or similar
• Experience deploying ML models at scale in self-driving or related fields
• Experience developing large-scale ML models (LLMs, VLMs, VLAs)
• Production-level coding under time-limited task schedules
• CV topics: multi-view geometry, camera calibration, depth estimation, NeRF, Gaussian splatting, SLAM
• Robot motion planning: trajectory optimization, sampling-based planning, MPC
• Temporal/sequential modeling
• Experience in self-driving challenges (Perception, Prediction, Mapping, Localization, Planning, Simulation)

キャリア成長観点

• 大規模な自動運転プラットフォームへ影響を与え、 Toyota の大量生産車両の挙動計画に直接寄与する機会
• データ戦略からトレーニング・デプロイまでのエンドツーエンドなMLライフサイクルを主導・改善できる成長機会
• 安全基準とコスト効率を両立させる設計・実装を通じ、先端AI技術と実運用の両方を経験可能
• ハイブリッド勤務・多部門連携環境を通じてリーダーシップや専門性を高め、モビリティ領域の上位職・技術系アーキテクトへキャリアパスが広がる