About this role
Summary: Develop closed-loop AI/ML optimization models to improve telemetry data quality and system performance in real time. The role involves designing ML models, building feedback systems, and analyzing multi-sensor data for fusion and monitoring applications.
Join BDAS to develop closed-loop AI/ML optimization models that continuously improve telemetry data quality and system performance in real time. You'll work directly with live sensor data (g-force, acceleration, location, temperature) as part of IDDMF's enrichment layer.
Location: Boulder, CO (Hybrid/Remote-eligible)
Responsibilities
- Design and train ML models for real-time data quality and performance optimization
- Build closed-loop feedback systems that adapt based on live data
- Analyze multi-sensor telemetry data for fusion and monitoring applications
- Collaborate with software engineers to integrate models into production pipelines
Qualifications
- Bachelor's or Master's in Data Science, Computer Science, Statistics, or related field
- Experience with Python-based ML frameworks (PyTorch, TensorFlow, scikit-learn)
- Familiarity with real-time/streaming data systems
- Bonus: experience with sensor data, telemetry, or defense/aerospace domains
Internship Opportunity: An internship track is also available for this role. A completed degree is not required for internship candidates — current students and early-career applicants with relevant coursework, projects, or experience are encouraged to apply and to note their interest in the internship in their application.