Machine Learning Engineer

Your New Role and Team

Sanctuary AI, a world leader in building dexterity-driven Physical AI for general purpose robots, is seeking Machine Learning (ML) Engineers to join our team of seasoned engineers, researchers, and scientists who are dedicated to tackling fundamental challenges in robotic perception, dexterous manipulation, planning, and reasoning.

As a member of the ML team, your role will focus on building robust systems for training and running ML policies on robots, and working closely with researchers to implement and deploy novel ML techniques into production. With access to our in-house robotic platforms, you’ll design, test, and refine software that connects state-of-the-art methods to real-world performance. This position offers a unique chance to contribute to both the engineering foundations and applied ML capabilities that drive our robots forward.

As part of this role, you will occasionally travel (typically one to two weeks at a time, several times per year) to collaborate closely with partners and teams in advancing critical projects.

Success Criteria

• Collaborate with cross-functional teams to identify opportunities for applying machine learning techniques to solve complex problems.

• Design, develop, and deploy machine learning models and algorithms to address specific business needs and challenges.

• Implement scalable and efficient software solutions to integrate machine learning models into production systems.

• Optimize and fine-tune machine learning algorithms for improved performance and accuracy.

• Conduct thorough testing and validation of machine learning models to ensure robustness and reliability.

• Stay updated on the latest developments and advancements in machine learning and communicate promising research directions to the team.

• Provide technical guidance and mentorship to junior team members.

Your Experience

Qualifications

• Master’s degree or Ph.D. in Computer Science, Engineering, Mathematics, or a related field.

• 3+ years of experience in machine learning methods, with specialization in areas such as reinforcement or imitation learning for dexterous manipulation, computer vision for robotics, or natural language processing.

• 4+ years of software engineering experience, with a focus on developing and deploying production-grade applications.

• Hands-on experience deploying ML models to production.

• Proficiency with ML frameworks and libraries (e.g., PyTorch, TensorFlow, scikit-learn).

• Experience with ROS2 and parallel computing (e.g., CUDA, OpenMP).

• Familiarity with cloud platforms (AWS, Azure, GCP) and distributed computing frameworks (e.g., Spark) is a plus.

• Demonstrated experience applying ML techniques in real-world systems is strongly valued. Publications are welcome but not expected for this role.

• Familiarity with robotics principles and technologies is highly desirable.

Skills

• Strong programming proficiency in Python and C++.

• Working knowledge of core machine learning techniques and algorithms (e.g., supervised/unsupervised learning, deep learning, reinforcement learning, natural language processing) and the ability to apply them effectively in software systems.

• Ability to optimize and fine-tune ML algorithms for performance and accuracy.

• Strong problem-solving skills and the ability to work effectively in a fast-paced, collaborative environment.

• Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.

• Leadership and mentorship ability, supporting the growth of junior team members.

Traits:

• Above all else, a consistently positive attitude and a willingness to do whatever it takes to create robust solutions to complex problems.

• Takes ownership and accountability, fostering the same in teammates.

• Empathetic listener with conflict resolution capabilities.

• Consistent bias for action, communication, and interpersonal savvy.

• Self-motivated and able to solve problems independently.

• Mission driven and passionate about bringing human-like intelligence to machines.