Senior/Staff Machine Learning Engineer, Dexterity

• Ideally, you will bring data-driven productization experience and help the team broadly in qualifying, deploying and updating models
• Degree in Computer Science, Electrical Engineering, or Mathematics 5+ years of industry experience applying machine learning to real-world, production systemsStrong Python skills and deep experience with PyTorch
• Ability to work fluently across ML tasks, e.g., classification, regression, ranking, segmentation, and structured prediction
• Strong engineering background with experience profiling, debugging, and optimizing model and pipeline performance
• Proven ability to design and maintain reliable systems, from model training to field deployment
• Experience with cloud-based infrastructure (AWS, GCP, Azure) and containerized environments (Docker)
• Familiarity with Linux, Git, CI/CD) and software development best practices (unit/acceptance/integration testing, code reviews)

Desirable

• As a Senior/Staff Machine Learning Engineer, you will be working on a myriad of challenges related to robot task and action planning
• You will leverage techniques from machine learning to solve hard sequential decision problems that require reasoning about the physical world and its dynamics
• You will also stay abreast of the latest progress in imitation learning, reinforcement learning, and other related fields in order to further develop Dexterity’s technology foundations in Physical AI
• Additionally, you will be responsible for updating and scaling our current ML pipelines to cover more scenarios and improve accuracy
• Dexterity's robotic solutions integrate data from a multitude of sensors, including RGB cameras, depth sensors, force-torque sensors, encoders, system telemetry and human input
• To better inform the planning algorithms, you may work on sensor fusion and state estimation techniques to leverage this multimodal sensory data
• You will also work closely with the data platform, physics simulation, and robot operations teams to develop effective and efficient ways to improve the system’s internal world model
• Dexterity has an expanding set of algorithmic challenges as we deploy new robotic applications, including areas such as:
• Improving packing algorithms to build taller, denser, more stable structures with a wider variety of objects
• Solving the logistics task of moving and sorting inventory throughout a warehouse
• Building models that understand physics and geometry for both short- and long-horizon tasks
• In addition to curating datasets and developing/improving machine learning models, you will be responsible for building data flywheels
• Design and implement machine learning solutions across Dexterity’s robotics stack, including but not limited to perception, decision-making, action scoring, and predictive modeling
• Own the full ML development cycle for these solutions: data curation, labeling, training, evaluation, deployment, and iteration
• Build performant training and inference pipelines using PyTorch, with production-readiness and scalability in mind
• Collaborate closely with robotics, data platform, and simulation teams to integrate ML into real-time, latency-sensitive robotic systems
• Use profiling, monitoring, and experiments to optimize model performance and reliability
• Ensure reproducibility, traceability, and modularity across training and serving pipelines
• Maintain clean, production-quality code in Python (and C++ where required)
• Help establish best practices for model versioning, dataset management, and ML operations