Machine Learning Engineer, Large Behavior Models - Data
Description For Machine Learning Engineer, Large Behavior Models - Data
Toyota Research Institute (TRI) is at the forefront of revolutionizing robotics through advanced machine learning and AI. We're seeking a Machine Learning Engineer to join our Large Behavior Models team, focusing on making general-purpose robots a reality. The role involves working with cutting-edge technology in robot manipulation, training large-scale foundation models, and developing sophisticated ML pipelines.
Our mission is to improve the quality of human life by creating robots that can assist with household tasks, help the elderly maintain independence, and operate reliably in unstructured environments. We're gathering extensive datasets of physical interaction and training large generative foundation models using multiple modalities including language, video, and audio.
The position offers an opportunity to work with a cross-functional team of experts in simulation, perception, controls, language, vision, and multimodal learning. You'll collaborate with top academic institutions like MIT, Stanford, and Berkeley, while contributing to groundbreaking research in robotics and AI. The role combines practical engineering with cutting-edge research, requiring both technical expertise and innovative thinking.
We offer competitive compensation ($165,760-$248,640/year for California-based roles) and comprehensive benefits including 401(k), paid time off, and annual bonuses. Our inclusive environment welcomes diverse backgrounds and experiences, fostering innovation and collaboration. Join us in creating the next generation of AI-powered capable robots that will transform how humans interact with technology.
Responsibilities For Machine Learning Engineer, Large Behavior Models - Data
- Collaborate with internal research scientists and partner labs at top academic research universities
- Build, improve, and robustify end-to-end integrated ML pipelines for training multimodal models at scale
- Build large-scale data pipelines to ensure data quality through automated validation, filtering, and deduplication
- Develop ML ecosystem from data ingestion to dataset management for large scale ML model training
- Train, finetune, and serve robot foundation models with a strong MLOps mindset
- Apply MLOps best practices to automate and monitor training, validation, and deployment processes
- Build processes for integrating collaboration-produced and open-source advancements
- Be a key member of the team and play a critical role in rapid progress
Requirements For Machine Learning Engineer, Large Behavior Models - Data
- 2+ years of professional ML engineering experience at an AI/ML-focused organization
- Familiarity with the state-of-the-art in behavior learning, language, and/or computer vision
- Experience training large-scale foundation models utilizing distributed training and high-performance optimization techniques
- Extensive practical experience with PyTorch
- Strong proficiency in Python and software development best practices
- Familiarity with cloud service and workflow for data pipelines, model serving and optimization
- An ability to move fast and switch between modes of rapid prototyping and robust implementation
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