Why this role stands out
This mid-senior Machine Learning Engineer role offers incredible growth potential by deploying cutting-edge AI directly into flight systems, allowing you to build robust MLOps pipelines and optimize algorithms for spacecraft hardware. You'll thrive here if you have a strong software engineering background and proven experience deploying ML models, collaborating with a talented team at a reputable company. Apply now to make a tangible impact on orbital systems and ground operations!
Quick overview
Job description
The Role
We are looking for a PhD-level Research Scientist to build the models behind ConstellationOS. You will develop forecasting and decision models for satellite link conditions and ground-network operations, and prove them against real data and physics-based baselines. Your work shows up in customer pilots and government evaluations.
Responsibilities
Develop and train machine learning models that forecast link conditions and support operational decisions.
Own data acquisition and preprocessing for telemetry, weather, atmospheric, and RF datasets.
Benchmark learned models against deterministic physics models and report results honestly, including failures.
Do simulation research for GNC and RF systems.
Work with academic groups and publish or present results
Turn research into code the platform team can ship.
Requirements
Ph.D. (or near completion) in Machine Learning, Applied Mathematics, Physics, Aerospace, Electrical Engineering, or a related field.
Publications or equivalent research output in forecasting, deep learning, reinforcement learning, or scientific ML.
Strong Python and PyTorch or JAX. Able to write research code others can run.
Experience with time-series, signal, or physical-system data is a plus.
U.S. person required (ITAR).
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