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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
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