Mid Level AI/ML Engineer, Onsite

About the Role

Technical Integrity is seeking an associate- or mid-level engineer with hands-on skills in machine learning, cloud infrastructure, and software development to help build AI capabilities for satellite operations. This role involves developing pipelines, infrastructure, and tools to bring machine learning into production for an expanding automated satellite operations capability.

The Opportunity

This is a hands-on engineering role working closely with software, data engineering, and mission operations teams. Responsibilities will include model development and deployment, building data processing workflows, and applying AI to satellite operations challenges. Early-career candidates with substantial project, research, or internship experience, as well as mid-level engineers with experience deploying production systems, are welcome. The scope of responsibilities will reflect your experience.

Key Responsibilities

• Build and maintain data pipelines supporting machine learning training, validation, and deployment.
• Help develop and deploy models using PyTorch, TensorFlow, or similar frameworks.
• Contribute to AWS infrastructure and containerized environments for training and inference.
• Implement MLOps workflows for model versioning, registration, deployment, and monitoring.
• Develop proofs of concept for predictive telemetry analysis, intelligent automation, and workflow integrations.
• Collaborate with software engineers and mission operations teams to integrate AI capabilities into satellite tracking and operations systems.
• Improve testing, observability, reliability, and performance as models move into production.

Requirements & Tech Stack

• Python experience and strong software engineering fundamentals.
• Practical experience with PyTorch, TensorFlow, or similar frameworks through professional work, research, internships, or substantial technical projects.
• Familiarity with AWS, Linux, and containers.
• Understanding of networking and security fundamentals.
• Familiarity with model training, evaluation, deployment, and monitoring, with an interest in building reliable, repeatable workflows.
• Ability to work onsite in Central Boulder five days a week.
• U.S. citizenship and ability to obtain and maintain a U.S. Government security clearance.

Qualifications

• A degree in Computer Science, Mathematics, Physics, Electrical Engineering, or a closely related technical discipline.
• A master’s degree or PhD is a plus.
• Exposure to ECS or EKS is a plus.
• Experience with CUDA, model optimization, distributed systems, or production ML deployments is helpful.
• Curiosity, clear communication, and a willingness to learn while contributing directly to engineering work.