Space Surveillance ML Engineer

Socket.dev; Denver (CO); On-site; USD 120,000 - 180,000; Full time

Job summary

Digantara U.S. is seeking an experienced Data Science Engineer to develop ML components and integration infrastructure for SDA analytics pipelines in Denver, Colorado.

The role focuses on trajectory-classification and anomaly-detection models that operate on orbit-determination output and on benchmarking frameworks for sparse data conditions. Collaborating with astrodynamics and embedded-systems staff, you will ensure models align with dynamical structure and deploy within onboard resource

Qualifications

• BS/MS in Computer Science, Applied Mathematics, Statistics, Aerospace Engineer, Physics, or a related quantitative field, plus 4+ years of applied ML experience.
• Strong Python and the scientific stack (NumPy, SciPy, pandas); fluency in at least one deep-learning framework (PyTorch preferred).
• Demonstrated experience building ML systems on time-series, sequential, or state-estimation-adjacent data.
• Sound evaluation methodology including calibration and uncertainty quantification.
• Software-engineering discipline for shared codebases: VCS, testing, reproducible environments.
• Clear technical writing for customer-facing deliverables.
• Must be able to obtain and hold a U.S. security clearance.

Responsibilities

• Develop AI/ML models for trajectory classification across orbit regimes and families, and for detection of anomalous dynamical behavior.
• Integrate and maintain end-to-end analytical pipelines spanning observation processing, hypothesis generation, orbit estimation, propagation, and classification; define interfaces, own the shared, reproducible codebase.
• Build benchmarking and evaluation frameworks: estimator convergence behavior, classification accuracy and confusion structure, false-positive/false-negative characterization, time-to-custody, and sensitivity to track gaps.
• Design experiments to distinguish genuine generalization from dataset artifacts and degraded-observation ablations.
• Produce calibrated confidence metrics suitable for downstream operational use.
• Partner with embedded-systems staff to characterize model complexity, memory footprint, and inference latency, and to identify quantization or deployment simplifications.
• Contribute machine-learning inputs to CONOPS and systems-engineering activities, including data-flow definition and model retraining considerations.

Job description

Digantara U.S. is seeking an experienced Data Science Engineer to develop ML components and integration infrastructure for SDA analytics pipelines in Denver, Colorado.

The role focuses on trajectory-classification and anomaly-detection models that operate on orbit-determination output and on benchmarking frameworks for sparse data conditions. Collaborating with astrodynamics and embedded-systems staff, you will ensure models align with dynamical structure and deploy within onboard resource