Senior Staff AI Algorithms Engineer
Dexterity is an enterprise Physical AI and robotics company deploying AI-powered industrial robots for logistics and manufacturing operations.
Funding history
Investors
About Dexterity, Inc.
Dexterity develops a full-stack Physical AI platform, including its Foresight world model and Mech industrial robot, for production material-handling work such as trailer loading and unloading, palletizing, depalletizing, aircraft loading and unloading, and singulation.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will design and prototype algorithms for learning, prediction, and planning. You will apply reinforcement learning, geometric reasoning, and optimization to robotic decision problems, balance technical approaches against operational constraints, test algorithms in simulation and on real robots, and improve experimentation tooling.
Requirements
- PhD or equivalent experience in machine learning, robotics, optimization, applied mathematics, or a related field
- Strong foundation in probability, statistics, optimization, reinforcement learning, imitation learning, and foundation models
- Ability to implement practical and testable code with Python and PyTorch or similar frameworks
- Ability to collaborate across engineering and research disciplines
Responsibilities
- Design and prototype algorithms for learning, prediction, and planning
- Apply reinforcement learning, geometric reasoning, and optimization methods to robotic decision problems
- Translate open-ended problems into practical technical approaches
- Balance modeling decisions with latency, reliability, and partial-observability constraints
- Build and test algorithms in simulation and real-robot environments
- Collaborate with product, software engineering, and robotics partners
- Contribute to internal knowledge, tooling, and experimentation pipelines
Hiring Process
Applications may be reviewed with AI tools; resumes and responses may be analyzed, and application materials assessed for inconsistencies or verification signals. The recruitment team uses these tools, while final hiring decisions are made by humans.