Embodied AI Lead / Robot Brain Lead

Your Role

As Embodied AI Lead or Robot Brain Lead, you will own the overall Embodied AI architecture for our platform:

• System 2 - vision-language(-action) models for task understanding, planning, and dialogue.
• System 1 - visuomotor policies for whole-body control and manipulation.
• World models - for imagination, planning, and predictive safety.

Additional information

You are both an architect and a hands-on technical leader, guiding a small team to turn cutting-edge research into robust, production-ready capabilities.

Key Responsibilities

Architecture & roadmap

• Design the overall Robot Brain architecture:
• System 2: VLM/LLM/VLA for semantic understanding and task planning.
• System 1: visuomotor control for locomotion and manipulation.
• World model integration for rollouts and safety.
• Define a short-term and long-term technical roadmap balancing innovation and deliverables.

Model strategy & implementation

• Make key decisions on model families and training strategies:
• E2E visuomotor, diffusion policies, transformer policies, VLA-based approaches, RL/BC hybrids.
• Lead the implementation and deployment of the first production version of the Robot Brain on at least one robot platform.
• Drive iterative improvements as we expand tasks and sites.

Cross-team integration

• Collaborate with Control & Robotics:
• Co-design skills (navigate, pick, place, open, inspect, etc.).
• Ensure Brain outputs are physically feasible and robust.
• Collaborate with Agent & Applications:
• Align Brain capabilities with real workflows and job definitions.
• Collaborate with Platform & Data:
• Define training data schemas and logging requirements.
• Build end-to-end training and deployment pipelines.

Safety, evaluation & reliability

• Define evaluation protocols for the Brain:
• Task success, robustness, long-horizon stability, safety incident metrics.
• Work with World Model & Safety teams to incorporate predictive safety and scenario-based testing.
• Ensure the Brain is observable, debuggable, and improvable in production.

Team leadership

• Hire, mentor, and lead a small Embodied AI team (3-6 engineers/researchers initially).
• Establish high standards for engineering quality, experimentation, and documentation.
• Represent the Embodied AI function in technical and cross-functional planning (product, hardware, operations).

Basic Qualifications

• Bachelor's or higher in CS, Robotics, EE, or related field.
• 5+ years in ML / robotics, including 2+ years in a lead / tech lead role.
• Deep experience in at least two of:
• Proven track record deploying ML models on real robotic hardware, not just simulation.
• Strong coding skills in Python and experience with PyTorch or JAX, multi-GPU training.
• Strong written and verbal communication; able to write clear design docs and align stakeholders.

Preferred Qualifications

• PhD or equivalent industry research experience in Robotics, AI, Machine Learning, or a related field.
• Hands-on experience with foundation models for robotics, such as VLMs, VLAs, or multimodal LLM-based agents applied to real-world embodied tasks.
• Experience building or scaling robot learning systems in production, including data collection at scale, sim-to-real transfer, and continuous learning loops.

Benefits

($180,000.00 - $250,000.00 DOE), plus benefits and incentive plans:

Perks + Benefits

• Healthcare + dental + vision benefits (Free for you/discounted for family)
• 401(k) options
• Casual dress code + relaxed work environment
• Culturally diverse, progressive atmosphere.