Designing, building, and operating AI
and machine learning-powered systems that enable real-time space domain awareness and drive customer-facing insights.
Developing scalable pipelines, deploying models into production, and integrating AI capabilities into operational systems.
Transforming large-scale sensor and orbital datasets into intelligent systems that detect patterns, identify anomalies, and generate predictive insights.
Owning the full lifecycle of AI solutions—from data and feature pipelines to model deployment, monitoring, and continuous improvement.

Must be eligible to obtain and maintain a U.S. personnel security clearance
B.S. or M.S. in Computer Science, Artificial Intelligence, Machine Learning, Engineering, Mathematics, Physics, or equivalent experience
5-7 years of experience in software engineering, machine learning engineering, or applied AI roles
Up-to-date familiarity with the latest developments in Agentic AI
Strong proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn)
Advanced experience with SQL and large-scale data processing
Proven experience developing and deploying production-grade machine learning models
Experience working with large-scale distributed data platforms (e.g., Databricks, Spark)
Strong understanding of statistical modeling, machine learning algorithms, and experimental design
Experience designing and implementing feature engineering pipelines and training workflows
Familiarity with MLOps practices, including model versioning, monitoring, and lifecycle management
Strong problem-solving skills and ability to translate ambiguous real-world problems into scalable AI solutions
Excellent communication skills, with the ability to influence technical and non-technical stakeholders.

Senior AI Engineer

Key skills