Senior Director, AI

About this role

Agility’s commercially deployed humanoids operate alongside teams in warehouses, manufacturing facilities, and distribution centers—tackling physically demanding and repetitive tasks while enabling workers to focus on higher-value work. With industry-leading safety standards and years of proven deployment data, we're pioneering a new era of automation that enhances human potential.

Overview

The Senior Director of AI will be a pivotal leader within our cutting-edge humanoid robotics company, driving the strategic direction and execution of all artificial intelligence and machine learning initiatives. This role requires a knowledgeable technologist and a skilled manager capable of championing and leading our existing high-performing team to develop the AI foundation for the next generation of humanoid robots. The successful candidate will be instrumental in defining the AI architecture, ensuring ethical implementation, and delivering robust, real-time AI capabilities that enable our robots to interact intelligently and safely with the world.

Core Responsibilities and Deliverables

Strategic Leadership and Vision

• Define and champion the overall AI strategy and roadmap in alignment with the company's product vision and business goals.

• Lead the selection and integration of advanced machine learning models, algorithms, and deep learning techniques relevant to embodied AI (e.g., perception, manipulation, natural language understanding).

• Foster a culture of innovation, rigorous research, and responsible AI development that supports the team's ongoing success.

• Ensure that all AI systems adhere to the highest standards of safety, privacy, and ethical guidelines.

• Partner with Hardware and Robot Software leadership to ensure the sensor suite and embedded compute are optimized for current and future AI model architectures.

Technical Execution and Development

• Oversee the design, development, and deployment of on-robot and cloud-based AI systems, leveraging the existing team's expertise.

• Establish MLOps best practices for efficient model training, deployment, monitoring, and iteration.

• Drive research into novel AI solutions for complex robotics challenges, such as real-time planning, human-robot interaction, and adaptive motor control.

• Deliver production-ready AI models that meet performance, latency, and reliability requirements for commercial deployment.

• Spearhead the Sim2Real strategy, utilizing physics-based simulation (e.g., MuJoCo, Isaac Sim) to train robust policies that transfer seamlessly to hardware.

• Accelerate our data flywheel strategy to combine teleoperation, synthetic data, and fleet learning to expand the fleet performance and reliability.

Team Building and Hiring

• Champion the existing team's talent and represent their needs to senior leadership.

• Develop a comprehensive hiring plan to staff and scale the AI team, including defining required roles (e.g., ML Engineers, Data Scientists, AI Researchers).

• Lead recruitment, mentorship, and career development for all members of the AI team.

• Manage the budget allocated for team salaries, equipment, and necessary infrastructure.

Resourcing and Budgeting

• Forecast and manage the budget for cloud computing resources (GPUs, TPUs) necessary for large-scale…