Machine Learning Engineer

Please Note: To conform with the United States Government Space Technology Export Regulations, the applicant must be a U.S. citizen, lawful permanent resident of the U.S., conditional resident, asylee or refugee (protected individuals as defined by 8 U.S.C. 1324b(a)(3)), or eligible to obtain the required authorizations from the U.S. Department of State.
At CesiumAstro, we are developers and pioneers of out-of-the-box communication systems for satellites, UAVs, launch vehicles, and other space and airborne platforms. We take pride in our dynamic and cross-functional work environment, which allows us to learn, develop, and engage across our organization. If you are looking for hands-on, interactive, and autonomous work, CesiumAstro is the place for you. We are actively seeking passionate, collaborative, energetic, and forward-thinking individuals to join our team.
We are looking for a Senior Machine Learning Engineer II to contribute to the development and deployment of machine learning solutions for our advanced distributed processing platforms. This role is highly collaborative, working closely with product, backend, and systems engineering teams to design, integrate, and maintain robust ML applications that support CesiumAstro’s mission. 

JOB DUTIES AND RESPONSIBILITIES

• Design, develop, and maintain deep learning pipelines for real-time data processing. 
• Evaluate and curate relevant datasets; establish model benchmarks to measure performance. 
• Improve observability and monitoring for deployed ML systems. 
• Develop, deploy, and maintain microservices that deliver ML capabilities to production systems. 
• Enhance tooling and orchestration for tuning, deployment, and scaling of ML pipelines. 
• Collaborate in research and development initiatives, contributing to new ML capabilities for aerospace and defense applications. 
• Document designs, workflows, and operational best practices to ensure maintainable and resilient ML systems. 

JOB REQUIREMENTS AND MINIMUM QUALIFICATIONS

• Bachelor’s or higher degree in Computer Science, Engineering, or related technical field. 
• 6+ years of professional experience developing production-ready ML systems in small to medium-sized organizations (additional experience required for larger organizations). 
• Proficiency in Python with demonstrated experience implementing ML algorithms in production environments. 
• Experience designing and maintaining APIs for ML services. 
• Hands-on experience deploying and managing ML workflows in Kubernetes environments.