Research Engineer developing agentic systems at Anthropic focused on LLMs and AI applications. Collaborating with researchers to enhance agent performance and tackle complex tasks.
TI
Hybrid Research Engineer – Simulation for Robot Learning
Posted 4 months ago
About the role
- Research Engineer developing AI-powered robots through simulation and Large Behavior Models at Toyota Research Institute. Collaborating on cutting-edge research in AI and robotics technologies.
Responsibilities
- Build, improve, and robustify end-to-end integrated ML pipelines for training multimodal (language, images, 3D, video, actions) models at scale.
- Develop and manage physics-based robot simulation environments enabling scalable training and evaluation of learning-based behavior models in realistic, physically grounded scenarios.
- Integrate and validate learned policies in simulation, assessing real-world applicability, generalization, and performance across diverse environments, tasks, geometries, and sensor viewpoints.
- Train, finetune, and serve robot foundation models with a strong MLOps mindset.
- Build processes for integrating collaboration-produced and open-source advancements and code into our internal stack.
- Collaborate with internal research scientists and our partner labs at top academic institutions and Toyota research labs to drive pioneering research at scale.
Requirements
- Bachelor's or master's degree in Computer Science, Robotics, Physics, or a related field.
- 2+ years of professional engineering experience at an AI/ML-focused organization.
- Strong proficiency in Python and experience with simulation frameworks such as Isaac Sim, PyBullet, MuJoCo, or similar.
- Hands-on experience with robotics simulation, reinforcement learning, or large-scale machine learning.
- Familiarity with state-of-the-art methods in behavior learning and/or computer vision.
- Experience integrating ML models into simulated or real-world environments.
- Extensive practical experience with PyTorch.
- Ability to alternate between rapid prototyping and production-quality implementation.
- Solid understanding of software engineering best practices, including testing, CI/CD, and documentation.
Benefits
- medical, dental, and vision insurance
- 401(k) eligibility
- paid time off benefits (including vacation, sick time, and parental leave)
- annual cash bonus structure
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