Machine Learning Engineer
The posting does not state a salary. This range is our estimate from the role, the location and the stack — treat it as a guide, not an offer.
- Level
- Mid
- Apply from
- United States
About the role
- Bridge the gap between AI research and production systems.
- Deploy and maintain ML models in production environments.
- Build robust MLOps pipelines for continuous integration.
- Optimize algorithms for low-latency inference.
- Collaborate with data scientists and flight software engineers.
Skills the posting asks for
- Python
- C++
- Docker
- MLOps
Summarised from the employer’s posting, which is reproduced in full below.
The employer’s full posting
The Role
We are looking for a Machine Learning Engineer to bridge the gap between AI research and production-grade flight systems. You will optimize, deploy, and scale machine learning models that directly impact Constellation’s orbital systems and ground operations.
Responsibilities
Deploy, monitor, and maintain ML models in production environments.
Build robust MLOps pipelines for continuous training and integration of models using telemetry data.
Optimize algorithms for low-latency inference on edge devices (spacecraft hardware).
Collaborate with data scientists and flight software engineers to integrate AI capabilities into core flight systems.
Requirements
B.S. or M.S. in Computer Science, Engineering, or equivalent experience.
Proven experience deploying machine learning models into production.
Strong software engineering skills in Python and C++.
Experience with cloud platforms, containerization (Docker), and MLOps tools.