DeepRec.ai
Head of AI
Location:
San Francisco Bay Area (On-site) Type:
Full-time Base Salary:
$350,000 - $450,000 (Plus Bonus & Equity)
About the Role Work with a company who are building AI systems with general physical ability
systems that do not merely analyze data, but actively explore, experiment, and engineer in the real world. The work spans robotics, machine learning, autonomous experimentation, and applied science, with a focus on enabling AI systems to generate new knowledge through physical interaction.
We are seeking a Head of AI to lead the design and execution of our intelligence stack across autonomous agents, learning systems, and real-world deployment. This is a senior, hands-on leadership role for someone who can define long-term AI strategy while remaining deeply involved in technical decision-making.
What Youll Do: AI Strategy & Architecture Own the end-to-end AI vision and roadmap, from foundational models to deployed autonomous systems. Define system architectures that integrate reinforcement learning, large models, perception, simulation, and physical feedback loops. Establish best practices for learning in data-scarce, high-cost, real-world environments.
Model Development & Deployment Lead development of: Reinforcement learning systems for long-horizon planning and control Large models for reasoning, planning, and tool use Autonomous agents capable of designing and executing physical experiments Drive simulation-to-real transfer and ensure robustness in physical deployment. Partner closely with robotics, hardware, firmware, and manufacturing teams to tightly couple AI with physical systems.
Team Leadership Build, mentor, and manage a team of senior AI researchers and engineers. Set a high technical bar while fostering a culture of rigorous experimentation and fast iteration. Translate ambiguous research goals into executable engineering plans.
Applied Impact Enable autonomous discovery across complex scientific and engineering domains. Ensure AI systems scale reliably and safely in real-world operational settings. Represent the AI organization internally and externally as a technical leader.
Who You Are You are a deeply technical leader who enjoys working at the intersection of AI, robotics, and the physical sciences, and who is motivated by problems that do not have clean abstractions or easy datasets.
Required Experience 10+ years of experience in AI/ML research or engineering with significant hands-on contributions. Deep expertise in one or more of: Reinforcement learning Large language or foundation models Autonomous or robotic systems Proven experience deploying AI systems in real-world, non-simulated environments. Strong proficiency in Python and modern ML frameworks (e.g., PyTorch).
Leadership & Approach Experience leading senior, highly technical teams. Ability to balance long-term vision with day-to-day technical execution. Comfortable operating in high-ambiguity, research-driven environments. Strong scientific intuition and commitment to empirical validation.
Why This Role Build foundational AI systems that interact with and learn from the physical world. Shape the direction of autonomous experimentation and discovery. Work alongside a deeply interdisciplinary team tackling consequential real-world problems. Influence the architecture and culture of a next-generation AI organization.
Location:
San Francisco Bay Area (On-site) Type:
Full-time Base Salary:
$350,000 - $450,000 (Plus Bonus & Equity)
About the Role Work with a company who are building AI systems with general physical ability
systems that do not merely analyze data, but actively explore, experiment, and engineer in the real world. The work spans robotics, machine learning, autonomous experimentation, and applied science, with a focus on enabling AI systems to generate new knowledge through physical interaction.
We are seeking a Head of AI to lead the design and execution of our intelligence stack across autonomous agents, learning systems, and real-world deployment. This is a senior, hands-on leadership role for someone who can define long-term AI strategy while remaining deeply involved in technical decision-making.
What Youll Do: AI Strategy & Architecture Own the end-to-end AI vision and roadmap, from foundational models to deployed autonomous systems. Define system architectures that integrate reinforcement learning, large models, perception, simulation, and physical feedback loops. Establish best practices for learning in data-scarce, high-cost, real-world environments.
Model Development & Deployment Lead development of: Reinforcement learning systems for long-horizon planning and control Large models for reasoning, planning, and tool use Autonomous agents capable of designing and executing physical experiments Drive simulation-to-real transfer and ensure robustness in physical deployment. Partner closely with robotics, hardware, firmware, and manufacturing teams to tightly couple AI with physical systems.
Team Leadership Build, mentor, and manage a team of senior AI researchers and engineers. Set a high technical bar while fostering a culture of rigorous experimentation and fast iteration. Translate ambiguous research goals into executable engineering plans.
Applied Impact Enable autonomous discovery across complex scientific and engineering domains. Ensure AI systems scale reliably and safely in real-world operational settings. Represent the AI organization internally and externally as a technical leader.
Who You Are You are a deeply technical leader who enjoys working at the intersection of AI, robotics, and the physical sciences, and who is motivated by problems that do not have clean abstractions or easy datasets.
Required Experience 10+ years of experience in AI/ML research or engineering with significant hands-on contributions. Deep expertise in one or more of: Reinforcement learning Large language or foundation models Autonomous or robotic systems Proven experience deploying AI systems in real-world, non-simulated environments. Strong proficiency in Python and modern ML frameworks (e.g., PyTorch).
Leadership & Approach Experience leading senior, highly technical teams. Ability to balance long-term vision with day-to-day technical execution. Comfortable operating in high-ambiguity, research-driven environments. Strong scientific intuition and commitment to empirical validation.
Why This Role Build foundational AI systems that interact with and learn from the physical world. Shape the direction of autonomous experimentation and discovery. Work alongside a deeply interdisciplinary team tackling consequential real-world problems. Influence the architecture and culture of a next-generation AI organization.