Are you passionate about pushing the boundaries of software in the world of robotics? Do you get excited about the prospect of deploying cutting-edge autonomy in real-world applications? Are you looking for an opportunity to lead a talented team in reimagining the future of human-robot interaction? 

As the Head of Software & Autonomy at Collaborative Robotics, you will be at the helm of our software and autonomy initiatives. This role encompasses a broad range of responsibilities, from on-robot software development to overseeing cloud-based software infrastructure, as well as advancing machine learning, perception, SLAM, and large language models (LLMs). Your expertise will be instrumental in bringing practical autonomy solutions to the field and scaling both software and systems for maximum impact.

Collaborative Robotics is a team of innovators and builders redefining the future of human-robot interaction. We are working to realize a world where robots are a trusted extension of your surroundings. They work, adapt, and react around you. Not the other way around.

We’re hiring virtually in the US, in addition to our San Francisco Bay Area, California office onsite.

Key Responsibilities:

• Lead and manage the software and AI engineering teams to design, develop, and deliver robotic systems, including on-robot and cloud-based infrastructure, machine learning, and autonomous systems.
• Implement and scale innovative solutions in machine learning, perception, SLAM, and LLMs.
• Scale software and system operations effectively, ensuring robust performance and reliability.
• Manage and inspire a distributed, remote team of software and research engineers, fostering a culture of innovation and excellence.
• Advocate for and implement simulation-driven development approaches.
• Collaborate with cross-functional teams to integrate software and autonomy solutions seamlessly.
• Establish and drive strategic vision and goals, with an emphasis on delivery and market impact.
• Keep abreast of industry trends and technological advancements, integrating them to enhance delivery.
• Effectively manage resources, timelines, and budgets, focusing on delivery metrics and milestones.

Minimum Qualifications:

• Bachelor’s degree in Computer Science, Robotics, Software Engineering, or a related field.
• At least 8 years in software development, with a specific focus on deployed autonomy systems.
• A minimum of 3 years in a leadership role, managing engineering teams and ensuring project delivery.
• Strong background in machine learning, AI, computer vision, and deploying and scaling cloud infrastructure and data analytics.
• Proficiency in programming languages such as Python, C++, or their equivalents.
• Demonstrated ability to solve complex problems, coupled with strong leadership and communication skills.
• A track record of delivering complex software projects punctually and within budget.
• A highly motivated team player with excellent oral and written communication skills.
• Enthusiasm for working in a dynamic start-up environment.
• Availability for occasional travel.

Preferred Qualifications:

• Advanced degree (Master’s or Ph.D.) in Computer Science, Robotics, AI, or a related field.
• Practical contributions to AI, machine learning, or robotics projects.
• Previous high-level leadership experience in a robotics or AI-focused organization, with a history of successful project delivery.
• Skilled in agile project management, lean methodologies, and resource optimization.
• Familiarity with robotic operating systems (ROS) and autonomous control systems.
• 3+ years managing ML research scientists and engineers.
• Experience in leading the development of transformer models for autonomy applications.

The annual base salary for this position is $225,000, plus equity and comprehensive benefits. Our salary ranges are determined by role and experience level. The range reflects the minimum and maximum target for new hire salaries for the position in the noted geographic area. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training.