PR/095148 | Machine Learning Engineer

Company
A reputable automotive Japanese company

Responsibilities

• Design and implement advanced ML models tailored for autonomous vehicles, leveraging deep learning and large-scale data.
• Deploy scalable and efficient ML models into the autonomous driving platform.
• Integrate cutting-edge technologies while ensuring compliance with strict safety and cost requirements.
• Contribute to the full ML development lifecycle—data strategy, training, optimization, and validation.
• Apply the scientific method and critical thinking to invent state-of-the-art deep learning solutions.
• Operate in a fast-paced environment, applying Agile development practices.
• Foster a collaborative, “giver” mindset, supporting teammates while driving results.
• Collaborate with Perception, Motion Planning, Simulation, Infrastructure, and Tooling teams to deliver unified solutions.

Requirements

• MS or PhD in Machine Learning, Computer Science, Robotics, or related fields, or equivalent industry experience.
• 3+ years of experience with Python, deep learning frameworks, and software engineering best practices. Proficiency in C++ for platform integration.
• 2+ years of experience with deep learning techniques (supervised/unsupervised learning, transfer learning, multi-task learning, deep reinforcement learning).
• 2+ years of experience across the end-to-end ML pipeline: data sampling, preprocessing, training, evaluation, deployment, and inference optimization.
• Strong communication skills, with the ability to convey technical concepts clearly and accurately.

Nice to Have

• Publications in top-tier ML/AI conferences (e.g., NeurIPS, CVPR).
• Proven success in deploying ML models at scale, ideally in self-driving or related domains.
• Familiarity with production-level coding under time-sensitive conditions.
• Experience with computer vision, including:
  • Multi-view geometry
  • Camera calibration
  • Depth estimation
  • Neural radiance fields, Gaussian splatting
  • SLAM (simultaneous localization and mapping)
  • Knowledge of robot motion planning methods such as trajectory optimization, sampling-based planning, or model predictive control.
  • Experience working with temporal/sequential data models.
  • Background in self-driving challenges: Perception, Prediction, Mapping, Localization, Planning, Simulation.

Benefits

• Competitive Salary – Based on experience
• Flexible Work Hours
• Paid Leave – 20 days/year (prorated)
• Sick Leave – 6 days/year (prorated)
• Holidays – Weekends, Japanese national holidays, and company-defined days
• Social Insurance – Health, pension, workers’ comp, unemployment, and long-term care
• Housing Allowance
• Retirement Benefits
• Rental Car Support
• In-House Training – Software and language learning programs