Salary
≈ $135k – $263k per year (Estimated)
Location
In office (Austin)
Seniority
Senior · 6+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
CesiumAstro is an aerospace technology company headquartered in Austin, Texas, and founded in 2017. The company develops and manufactures software-defined active phased array communication systems, including satellites, terminals, and reconfigurable processing units for space, airborne, and ground missions. It serves commercial and defense sectors with high-throughput connectivity solutions and operates manufacturing facilities in the United States to support domestic supply chains.
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.
- Strong communication skills with the ability to clearly articulate complex technical ideas.
- Ability to work effectively in a collaborative, Agile engineering team.
PREFERRED EXPERIENCE
- 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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