About the role
- 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
- 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
Benefits
- Health, dental, vision
- HSA and FSA
- Company stock options
- Life, disability and retirement plans- 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
- Proficiency in Python with demonstrated experience implementing ML algorithms in production environments
- 6+ years of professional experience developing production-ready ML systems in small to medium-sized organizations (additional experience required for larger organizations)
- Ability to work effectively in a collaborative, Agile engineering team
- Hands-on experience deploying and managing ML workflows in Kubernetes environments
- Bachelor’s or higher degree in Computer Science, Engineering, or related technical field
- Strong communication skills with the ability to clearly articulate complex technical ideas
- Experience designing and maintaining APIs for ML services
- Knowledge of microservice architectures and distributed data systems
- Familiarity with aerospace or defense applications of ML systems
- Track record of contributing to early-stage or rapidly scaling teams
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