Machine Learning Software Engineer Jobs in Arizona

Prime Solutions Group (PSG), Inc. is an innovative digital engineering company founded in 2007 and headquartered in Goodyear, AZ. We specialize in advanced sensing, AI/ML, and digital engineering solutions, partnering with many of the nation’s leading defense companies to deliver mission-critical technology.

Our work spans the full system lifecycle—from R&D to operational deployment—supporting the Department of Defense, Intelligence Community, and federal partners. At PSG, you’ll join a small, agile team where your contributions have a direct impact while working alongside top-tier engineering talent.

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.

• 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

• 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

• 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

At PSG, you’re not just taking a job—you’re building technology that matters.

• 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

Bring your machine learning expertise to PSG and help deliver the next generation of secure, intelligent, mission-driven systems.

Salary Description

Salary range starts at $110,000 with the potential for higher compensation based on experience, skills, and mission needs.