Senior AI Engineer

🕒 June 26

🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

🤖 AI Engineer

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LeoLabs

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2016

🚀 Aerospace

🔧 Hardware

☁️ SaaS

Aerospace • Hardware • SaaS

LeoLabs is a commercial provider of persistent orbital intelligence and space domain awareness services. The company operates a network of ground-based, rapidly deployable radars and a cloud-based, AI-enabled platform to track and catalog objects in low Earth orbit, deliver real-time conjunction alerts, threat assessments, launch support, and space traffic management data for commercial and government customers. LeoLabs combines radar hardware, authoritative datasets, and SaaS analytics to help operators protect assets, avoid collisions, and manage launch and on-orbit operations.

📋 Description

• Designing, building, and operating AI- and machine learning-powered systems • Enabling real-time space domain awareness and driving 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

• 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.

🏖️ 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