Senior AI Engineer

This is a fully remote position, open to applicants in California.

📋 Description

• Design, train, and assess multimodal foundation models that facilitate multi-robot mission execution.

• Lead model development choices, encompassing model architectures, data mixtures, curriculum design, and training methodologies based on thorough experimentation.

• Curate and create extensive training datasets utilizing both synthetic and real-world data sources.

• Develop memory, communication, planning, and tool-use capabilities for AI agents functioning within teams of robots.

• Maintain a strong focus on evaluation: create benchmarks, metrics, and testing methodologies that support rapid iteration across the team.

• Construct and enhance simulation environments aimed at synthetic data generation, evaluation, and reinforcement learning.

• Convert foundational research into deployable, real-time perception and decision-making systems.

• Collaborate with engineering, robotics, and mission teams to merge AI systems with onboard autonomy stacks.

• Execute field trials and mission operations to validate system performance under real-world conditions.

⛳️ Requirements

• Over 6 years of practical experience in building and deploying AI models, including a minimum of 2 years working with multimodal models or agentic AI systems.

• Expertise in Python, PyTorch, and contemporary machine learning infrastructure.

• Experience in training, fine-tuning, and evaluating large-scale deep learning models utilizing distributed compute infrastructure.

• Proven history of enhancing model performance through data curation, training strategy, evaluation design, and rigorous experimentation.

• Strong understanding of modern model training techniques such as SFT, DPO, and RLVR.

• Demonstrated capability to transition research from prototype to product in fast-paced environments.

• BS, MS, or PhD in Computer Science, Engineering, Mathematics, Physics, or a related technical field, or equivalent practical experience. Advanced graduate research in AI, robotics, or machine learning is an advantage.

• Bonus: Experience in developing closed-loop simulation, evaluation, or reinforcement learning environments for agentic or physical AI systems.

• Must be a U.S. Person due to necessary access to U.S. export controlled information or facilities.

🏝️ Benefits

• Competitive compensation package that includes base salary and bonus.

• Meaningful equity options.

• Comprehensive medical, dental, and vision plans with no paycheck contribution required.

• Competitive paid time off (PTO) and a company holiday calendar.

• Unlimited AI tokens.

• Daily catered lunch and a fully stocked kitchen.

• Electric vehicle (EV) charging available.

• Relocation assistance offered (subject to role eligibility).