Machine Learning Systems Research Intern at Red Hat working on AI inference and model optimization techniques. Collaborating with experts in the field while gaining hands - on experience in applied ML research.
About the role
- Machine Learning Engineer developing and optimizing ML systems for autonomous vehicles. Join Toyota’s mission of transforming mobility through human-centric innovation.
Responsibilities
- Design, build, and maintain ML pipelines that produce training and evaluation data for behavior and prediction models, including ETL, feature extraction, augmentation, and labeling workflows.
- Implement auxiliary pipelines for model validation, metric computation, and on-road performance integration.
- Design and develop advanced machine learning models in the behavior space, specifically tailored for autonomous vehicles, utilizing deep learning and large-scale data analysis.
- Deploy scalable and efficient ML models on our autonomous vehicle platform.
- Integrate modern technologies with rigorous safety standards while maintaining cost efficiency.
- Oversee the development of new ML models end-to-end, from data strategy and initial development to optimization, production platform validation, and fine-tuning based on metrics and on-road performance.
- Lead large, multi-person projects and significantly influence the overall motion planning architecture and technical direction.
- Enable and support other engineers by coaching, leading by example, and providing high-quality code and design document reviews, as well as delivering rigorous reports from ML experiments.
- Contribute significantly to the development of essential components for end-to-end ML training and deployment, from data strategy to optimization and validation.
- Be a champion of the scientific method and critical thinking to invent state-of-the-art deep learning solutions.
- Work in a high-velocity environment and employ agile development practices.
- Collaborate closely with teams such as Perception, Simulation, Infrastructure, and Tooling to drive unified solutions.
Requirements
- MS or PhD in Machine Learning, Computer Science, Robotics, or related quantitative fields, or equivalent industry experience.
- 3+ years of experience with Python, major deep learning frameworks, and software engineering best practices.
- Built robust data pipelines, ETL workflows, and integration systems to support behavior prediction models
- Expertise with deep learning approaches, such as supervised/unsupervised learning, transfer learning, multi-task learning, and deep reinforcement learning.
- Good understanding of learning-based planning approaches, including imitation learning, reinforcement learning, and state-of-the-art techniques for sequential modeling, such as Transformer architectures.
- Practical experience with ML training and evaluation workflows, including data sampling, preprocessing, and reproducible experiment management.
- 3+ years of experience covering machine learning workflows, data sampling and curation, preprocessing, model training, ablation studies, evaluation, deployment, and inference optimization.
- Comfortable writing C++ code for integration with our autonomous vehicle platform.
- Passion for self-driving car technology and its potential to impact humanity.
- Strong communication skills with the ability to articulate concepts clearly and precisely.
Benefits
- Excellent health, wellness, dental and vision coverage
- A rewarding 401k program
- Flexible vacation policy
- Family planning and care benefits
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