Senior AI Engineer

Why LeoLabs?

At LeoLabs, we’re building the living map of activity in space. Through our proprietary global radar network and AI-enabled analytics platform, we collect millions of measurements daily on more than 25,000 objects in low Earth orbit (LEO). Our radar-powered intelligence protects billions in assets, monitors adversarial behavior, and ensures safe operations for commercial and government missions.

We’re not just building technology, we are redefining global security, safety, and transparency in space. As orbital activity accelerates and threats grow more complex, LeoLabs is a trusted partner for Space Domain Awareness, Space Traffic Management, and Satellite Operations for top-tier space operators and allied defense organizations.

If you're looking to work on mission-critical challenges at the forefront of aerospace, national security, and AI, your impact starts here.

The Opportunity 

We are seeking an experienced and mission-driven Senior AI Engineer to join LeoLabs’ growing Insights team. You will play a critical role in designing, building, and operating AI- and machine learning-powered systems that enable real-time space domain awareness and drive customer-facing insights. 
 
You will work at the intersection of machine learning, data engineering, and software engineering—developing scalable pipelines, deploying models into production, and integrating AI capabilities into operational systems. This includes transforming large-scale sensor and orbital datasets into intelligent systems that detect atterns, identify anomalies, and generate predictive insights. 
 
This role is highly hands-on and systems-oriented, with a focus on helping to define and drive LeoLabs’ utilization of the latest Agentic AI technology.

You will own the full lifecycle of AI solutions—from data and feature pipelines to model deployment, monitoring, and continuous improvement—while helping define best practices for applied AI across LeoLabs.   

Qualifications 

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 

Preferred Qualifications 

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 

Within 1 Month, You’ll 

Complete onboarding to gain deep familiarity with LeoLabs’ mission, products, and data ecosystem 

Set up development environments, data access, and ML tooling within the Databricks platform 

Review existing data pipelines, feature engineering workflows, and deployed models 

Begin contributing to model evaluation, analysis, or incremental improvements 

Within 3 Months, You’ll 

Develop a strong understanding of LeoLabs’ data architecture, AI/ML use cases, and operational constraints 

Lead development of new models or enhancements to existing systems 

Design and implement feature pipelines and training datasets for key problem areas 

Partner with data engineering to improve data quality, scalability, and pipeline reliability 

Within 6 Months, You’ll 

Own end-to-end delivery of AI/ML solutions, from problem framing through production deployment 

Deploy and monitor models in production, ensuring reliability and performance 

Optimize model performance through advanced feature engineering, tuning, and experimentation 

Mentor junior team members and contribute to team best practices 

Within 12 Months, You’ll 

Act as a technical leader in applied AI/ML within the Insights team 

Drive adoption of best practices in model development, MLOps, and reproducibility 

Identify and lead high-impact Agentic AI initiatives that enhance space domain awareness capabilities 

Perks and Benefits

Global workforce: flexible remote/hybrid opportunities

Work on complex, meaningful missions with real-world impact

Unlimited paid time off for most roles

Competitive salary and equity packages

Comprehensive health, dental, and vision coverage

Access to the forefront of commercial space operations and defense innovation

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identify, national origin, disability, or status as a protected veteran.