Senior Machine Learning Engineer
About The Position
Turn machine learning into real-world mission capability. PSG is seeking a Machine Learning Engineer to design, build, and deploy AI/ML solutions that power mission-critical systems. This role focuses on taking models from concept to production—developing pipelines, integrating models into software systems, and ensuring performance, scalability, and reliability in real-world environments. You’ll work at the intersection of machine learning, software engineering, and DevSecOps, collaborating with cross-functional teams to deliver secure, production-ready AI solutions supporting national security missions.
Requirements
- U.S. Citizenship
- Active Top Secret Clearance (SCI eligibility; CI Poly preferred or ability to obtain)
- Bachelor’s degree in Computer Science, Engineering, Data Science, or related field
- 4+ years of experience in:
- Machine Learning Engineering
- Applied AI/ML development
- Production ML systems
- Strong Python skills and experience with ML libraries (NumPy, pandas, scikit-learn, PyTorch, TensorFlow)
- Experience developing, training, and deploying ML models in real-world applications
- Solid understanding of the ML lifecycle (data ? training ? validation ? deployment ? monitoring)
- Experience building maintainable, production-quality software
- Familiarity with Docker and cloud environments (AWS, Azure, or GCP)
- Experience working in Agile and CI/CD environments
- Strong problem-solving, communication, and collaboration skills
Nice To Haves
- Master’s degree in a related field
- Experience with computer vision, image/video analytics, or sensor data (e.g., RF, SAR)
- Experience transitioning models from research to production environments
- Familiarity with experiment tracking, model versioning, and reproducibility practices
- Experience with GPU-based ML workflows and cloud ML platforms
- Background in defense, intelligence, or other regulated environments
Responsibilities
- Design, build, and maintain ML pipelines for data preparation, training, evaluation, and deployment
- Develop and optimize ML models and applications using Python and frameworks like PyTorch or TensorFlow
- Integrate models into production systems (APIs, batch pipelines, real-time services)
- Implement model validation, evaluation metrics, and performance monitoring
- Improve model accuracy, scalability, and efficiency through tuning and data strategy improvements
- Collaborate with data engineers and domain experts to prepare and validate datasets
- Partner with DevSecOps/MLOps teams to deploy ML solutions in secure environments
- Troubleshoot model and pipeline issues; perform root cause analysis and optimization
- Contribute to technical documentation, test plans, and operational runbooks
- Participate in design reviews, architecture discussions, and Agile development processes
- Mentor junior engineers and promote engineering best practices
Benefits
- Competitive compensation & benefits
- 9/80 flexible work schedule
- Professional development & tuition assistance
- Small, agile team with high ownership and visibility
- Work on mission-critical systems supporting national security
- Opportunities to grow across AI/ML, software engineering, and platform development
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Number of Employees
1-10 employees
