Senior Staff Machine Learning 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 implement machine-learning solutions across robotic perception, decision-making, action scoring, and prediction. You will own data curation, labeling, training, evaluation, deployment, and iteration; build scalable PyTorch pipelines; optimize reliability and performance; and establish model, dataset, and ML operations practices.
Requirements
- Degree in Computer Science, Electrical Engineering, or Mathematics
- 5+ years of industry experience applying machine learning to production systems
- Strong Python and PyTorch experience
- Experience with classification, regression, ranking, segmentation, and structured prediction
- Experience profiling, debugging, and optimizing models and pipelines
- Experience designing reliable systems from model training through field deployment
- Experience with AWS, GCP, Azure, or cloud infrastructure
- Experience with Docker
- Familiarity with Linux, Git, CI/CD, testing, and code review
Responsibilities
- Design and implement machine-learning solutions across perception, decision-making, action scoring, and predictive modeling
- Own data curation, labeling, training, evaluation, deployment, and iteration
- Build scalable training and inference pipelines with PyTorch
- Integrate machine learning into real-time robotic systems
- Use profiling, monitoring, and experiments to optimize performance and reliability
- Ensure reproducibility, traceability, and modularity across training and serving pipelines
- Maintain production-quality Python and C++ code
- Establish practices for model versioning, dataset management, and ML operations
- Curate datasets, develop machine-learning models, and build data flywheels
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.