Lead Perception Engineer
Teleo, a Havoc company, provides supervised-autonomy technology that retrofits heavy equipment for remote and semi-autonomous operation.
Funding history
About Teleo
Teleo supplies a full-stack system—retrofit hardware, mesh connectivity, remote command center, and the Teleo Insite analytics platform—for fleet-scale supervision of heavy machinery in construction, mining, logistics, and related industries.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will adapt and develop multimodal perception algorithms for construction and mining operations. You will train models, build auto-annotation tools, define evaluations, drive active learning and data selection, and integrate perception systems with MLOps for continuous deployment.
Requirements
- Master's degree or higher in Computer Science, Computer Engineering, Robotics, Electrical Engineering, or a related technical field
- 3+ years in applied machine learning with large-scale datasets
- Python and PyTorch proficiency
- Experience shipping perception or machine-learning systems into production
- Systems-level understanding of data, models, and infrastructure
- Auto-annotation techniques using VLM-based labeling
- Model evaluation across failure modes and edge cases
- Perception experience with detection, segmentation, depth, or tracking
- Multimodal data experience with camera, LiDAR, and radar
Responsibilities
- Adapt and extend perception algorithms for the operational domain
- Develop novel multimodal perception algorithms
- Train models as the operational domain evolves
- Develop auto-annotation and auto-labeling tools using VLMs
- Define evaluation protocols correlated with on-ground performance
- Drive active learning and data selection
- Integrate perception systems with MLOps for continuous deployment