ML/Data Infrastructure Engineer
Core
Build and operate data and ML infrastructure to transform drone inspection data into AI capabilities for hazardous environment surveying.
Role type
ML/Data Infrastructure Engineer
Builds
Data pools, labeling workflows, training infrastructure, model lifecycle tooling, and developer platforms for Spatial AI models.
Domain
Robotics / UAS (Unmanned Aerial Systems) / AI Infrastructure
Deliverable
production ML models
Required skills
Python, data engineering, MLOps, cloud storage (AWS S3), data processing, ML lifecycle management, Docker, CI/CD, infrastructure-as-code
Preferred skills
MLflow, DVC, SageMaker, annotation platforms, embedded model deployment, LLM pipeline orchestration
Technologies
AWS, S3, Docker, CI/CD tools, MLflow, DVC, SageMaker
Responsibilities
Own data ingestion, organization, curation, validation, and versioning; host labeling tools and manage annotation workflows; automate ML training, evaluation, and experiment tracking; build tooling for model deployment; monitor model performance and feedback loops; provide developer platforms for Spatial AI engineers.
Seniority
Mid-level, hands-on IC