TS/SCI ML Engineer — Hybrid, Mission-Focused

Grey-Matters-Defense-Solutions; Centennial (CO); Hybrid; USD 154,000 - 195,000; Full time

Benefits offered by this job

SEP IRA contribution

Health benefits

Employee assistance program

Employee discount

Health savings account

Referral program

Job summary

Grey Matters Defense Solutions, LLC is seeking a Machine Learning Engineer to address Intelligence Community and DoD problems using a blend of FOSS, GOTS, and COTS software and hardware.

You will contribute to the full AI lifecycle from research to deployment, designing experiments, training models, and integrating them into production environments in a hybrid Centennial, Colorado setting.

Qualifications

• U.S. citizenship is required.
• Active Top Secret security clearance (SSBI/Tier 5).
• Bachelor's degree in a related technical field.
• 7+ years of professional experience with Python.
• 4+ years of hands-on experience with PyTorch or another ML/DL framework.
• Experience training customized state-of-the-art AI models on real-world datasets.

Responsibilities

• Support end-to-end model development: architecture selection, training, evaluation, and iteration against mission problems.
• Design and run rigorous experiments with baselines and ablations and clear reporting for program decisions.
• Package and deploy models into operational environments and improve them over time.
• Collaborate with data engineers to support data selection, pre-processing, curation, and ETL for AI/ML development.

Skills

Python

PyTorch

Unix/Linux

Data structures

Algorithm design

Analytical skills

Communication skills

Problem solving

Education

Bachelor's degree in a related technical field

Master's or doctoral degree in CS/DS/Math/Phys/related field

Tools

N/A

Job description

Grey Matters Defense Solutions, LLC is seeking a Machine Learning Engineer to address Intelligence Community and DoD problems using a blend of FOSS, GOTS, and COTS software and hardware.

You will contribute to the full AI lifecycle from research to deployment, designing experiments, training models, and integrating them into production environments in a hybrid Centennial, Colorado setting.