Senior AI Engineer

LeoLabs is building a living map of activity in space through its global radar network and AI-enabled analytics platform. They are seeking an experienced Senior AI Engineer to design and operate AI systems for space domain awareness and insights, focusing on machine learning and data engineering.

Responsibilities:

• 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
• Helping define best practices for applied AI across LeoLabs

Requirements:

• 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
• Experience building Agentic AI systems for time-series, anomaly detection, or predictive modeling
• Familiarity with Databricks ML, MLflow, or similar ML lifecycle platforms
• Experience deploying models into production systems with real-time or near-real-time constraints
• Background working with sensor, telemetry, or geospatial/orbital datasets
• Experience mentoring junior data scientists or leading technical initiatives
• Familiarity with streaming data systems (e.g., Kafka, Spark Structured Streaming)
• Background in orbital mechanics, aerospace, physics, or applied mathematics
• Active U.S. security clearance or ability to obtain one