Toyota Research Institute (TRI) is seeking Machine Learning Research Interns to help bring end-to-end ML models (pixels to trajectories) into robust, testable, and deployable systems for automated driving. This role is crucial for advancing innovation and transformation in Toyota's mobility solutions by bridging research with practical product development.
Requirements
- Proficiency in Python for implementing and evaluating research ideas.
- Experience with ML frameworks such as PyTorch.
- Understanding of version control, testing, and software engineering fundamentals.
- Experience in ML engineering workflows: data sampling and curation, pre-processing, model training, ablation studies, evaluation, deployment, inference optimization.
- Understanding of debugging and profiling on NVIDIA CUDA stack.
- Hands-on experience with metrics dashboards, experiment tracking, and ML ops tooling (e.g., Weights & Biases, MLflow, Metaflow).
- Hands-on experience working with robotics or real-world sensor data (e.g., video, lidar, IMU, or radar).
Responsibilities
- Conduct ambitious research to advance the state-of-the-art in using new capabilities in generative modelling for end-to-end planning from vision in automated driving.
- Implement scalable end-to-end architectures that process raw sensor data to generate vehicle trajectories, addressing the challenges of long-tail driving scenarios with low data coverage.
- Prototype, validate, and iterate on model architectures using imitation learning, and large-scale data, ensuring robust performance across diverse scenarios.
- Perform closed-loop evaluations in sensor simulations and real-world testing environments.
- Explore multi-modal and language-conditioned models to broaden the applicability of end-to-end policies, leveraging external data sources and transfer learning to enhance generalization.
- Contribute to the implementation, evaluation, and integration of ML-based components for perception, planning, and control; with simulation-based testing.
- Work closely with researchers, data engineers, and autonomy engineers to ensure models scale from prototype to production.
Other
- Currently pursuing a Ph.D. or equivalent experience in Computer Science, Robotics, Engineering, or a related field.
- Passion for collaborative engineering and building reliable ML systems that support real-world autonomy.
- Summer 2026 paid 12-week internship opportunity.
- Hybrid in-office role.
- Please include links to any relevant open-source contributions or technical project write-ups with your application.
