AI/ML Software Engineer

Role Overview

Bandelier Technologies builds quantum sensing systems for defense applications. Our QT Guardian platform uses entangled photon coincidence measurements and AI/ML to detect and classify timing drift in distributed networks — complementing classical synchronization protocols like White Rabbit and PTP with an independent verification layer.

This role covers two workstreams: quantum timing integrity monitoring, building models that analyze coincidence observables to detect picosecond-scale drift; and sensor fusion for GPS-free navigation, integrating quantum magnetometers, inertial sensors, and other modalities. You will work closely with the National Laboratories, industry partners, and key stakeholders from DOW and DOE.

Key Responsibilities

• Design, train, and deploy transformer-based sequence models for temporal coincidence feature analysis drift classification, residual timing estimation, and calibrated uncertainty quantification
• Build real-time inference pipelines meeting sub-10-second detection latency under deployed fiber conditions
• Develop sensor fusion pipelines integrating heterogeneous quantum and classical sensing modalities at different sampling rates
• Build and maintain data infrastructure for collecting, labeling, and versioning experimental sensor datasets
• Benchmark AI models against classical baselines (parametric peak fitting, Kalman trackers, likelihood estimators)
• Develop coincidence counting and signal processing pipelines for quantum network imaging experiments
• Collaborate with LANL researchers and hardware partners to define data interfaces and ML approaches
• Contribute to technical reporting, proposals, and publications as needed

Required Qualifications

• Strong time-series and sequence modeling background — PyTorch, JAX, or TensorFlow
• Experience with uncertainty quantification: calibrated prediction intervals, not just point estimates
• Signal processing fundamentals — comfort with noisy, low-SNR physical sensor data
• Real-time inference and deployment experience
• U.S. citizenship (security clearance eligibility required)

Preferred Qualifications

• MS or PhD in Computer Science, Electrical Engineering, Applied Physics, or related field
• 3+ years building and deploying ML models in production or research environments
• Experience with transformer architectures for sequence modeling
• Sensor fusion techniques: Kalman filtering, particle filters, or learned fusion architectures
• Physics-informed or scientific ML — experience with physical sensor data beyond standard CV/NLP
• Background in quantum optics, photon counting, or timing systems
• Familiarity with anomaly detection under sparse data conditions

Why Bandelier

You will work on novel quantum sensing hardware alongside national lab scientists, with access to real deployed infrastructure for validation. This is an early-stage company with direct ownership and a clear path from research to field deployment.

Security & Eligibility

Many Bandelier positions require the ability to obtain a U.S. government security clearance. Security clearances may only be granted to U.S. citizens. Applicants who accept a conditional offer of employment may be subject to government security investigation(s) and must meet eligibility requirements for access to classified information.