Job Requirements
Goodyear, AZ
Top Secret Polygraph not specified
Mid Level Career (5+ yrs experience)
$110,000 - $180,000
Job Description
Build the platforms that power real-world AI.
PSG is seeking a Senior MLOps Engineer to lead the design, deployment, and optimization of machine learning platforms and pipelines supporting mission-critical systems. In this role, you’ll enable AI/ML capabilities to move seamlessly from development to production by building secure, scalable, and automated infrastructure.
You’ll work at the intersection of MLOps, DevSecOps, and cloud engineering, partnering with ML engineers, software developers, and security teams to deliver reliable, compliant, and high-performing AI systems in complex environments.
What You’ll Do
- Architect and maintain scalable ML pipelines for training, evaluation, deployment, and retraining
- Build and manage CI/CD pipelines for ML workflows, including automated testing and release controls
- Deploy and support containerized ML services using Docker, Kubernetes, and cloud platforms
- Implement Infrastructure-as-Code (IaC) for compute, storage, networking, and GPU-enabled environments
- Establish reproducibility across datasets, models, code, and runtime environments
- Integrate monitoring and observability for ML systems (latency, throughput, resource usage, model performance)
- Partner with ML and software teams to transition models into production environments
- Ensure ML platforms meet security and compliance standards (IAM, secrets management, system hardening)
- Troubleshoot complex pipeline, infrastructure, and deployment issues; drive root cause resolution
- Evaluate and implement modern MLOps tools, frameworks, and best practices
- Develop technical documentation, architecture diagrams, and operational runbooks
- Mentor junior engineers and contribute to architecture reviews and technical planning
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:
- MLOps or ML platform engineering
- DevOps/DevSecOps supporting ML workloads
- Cloud infrastructure engineering for data/ML systems
- Experience with CI/CD tools (GitLab CI, Jenkins, GitHub Actions)
- Proficiency with Infrastructure-as-Code (Terraform, Ansible, or similar)
- Experience with Docker and Kubernetes
- Hands-on experience with AWS, Azure, or GCP (including GPU-based workloads)
- Strong understanding of the ML lifecycle (training ? deployment ? monitoring ? retraining)
- Scripting experience (Python, Bash, or PowerShell)
- Familiarity with security best practices in regulated environments
- Strong problem-solving, communication, and collaboration skills
Preferred Qualifications
- Master’s degree in a related field
- Experience with ML orchestration and tooling (Airflow, Kubeflow, MLflow, etc.)
- Experience with model registries, experiment tracking, and reproducibility frameworks
- Familiarity with RMF, STIGs, or other compliance frameworks
- Experience with observability tools (Prometheus, Grafana, ELK, etc.)
- Background supporting AI/ML systems in defense, intelligence, or high-assurance environments
- Relevant certifications (AWS DevOps Engineer, AWS ML Specialty, Kubernetes, etc.)
Why Join PSG?
At PSG, you’re not just taking a job—you’re enabling the future of AI in national security.
- Competitive compensation & benefits
- 9/80 flexible work schedule
- Professional development & tuition assistance
- Small, agile team with high ownership and impact
- Work on mission-critical AI/ML systems with real-world impact
- Opportunities to grow into technical leadership roles
Bring your MLOps expertise to PSG and help build secure, scalable, mission-driven AI systems that make a difference.
Salary Description
Salary range starts at $110,000, with the potential for higher compensation based on experience, skills, and mission needs.
PSG is seeking a Senior MLOps Engineer to lead the design, deployment, and optimization of machine learning platforms and pipelines supporting mission-critical systems. In this role, you’ll enable AI/ML capabilities to move seamlessly from development to production by building secure, scalable, and automated infrastructure.
You’ll work at the intersection of MLOps, DevSecOps, and cloud engineering, partnering with ML engineers, software developers, and security teams to deliver reliable, compliant, and high-performing AI systems in complex environments.
What You’ll Do
- Architect and maintain scalable ML pipelines for training, evaluation, deployment, and retraining
- Build and manage CI/CD pipelines for ML workflows, including automated testing and release controls
- Deploy and support containerized ML services using Docker, Kubernetes, and cloud platforms
- Implement Infrastructure-as-Code (IaC) for compute, storage, networking, and GPU-enabled environments
- Establish reproducibility across datasets, models, code, and runtime environments
- Integrate monitoring and observability for ML systems (latency, throughput, resource usage, model performance)
- Partner with ML and software teams to transition models into production environments
- Ensure ML platforms meet security and compliance standards (IAM, secrets management, system hardening)
- Troubleshoot complex pipeline, infrastructure, and deployment issues; drive root cause resolution
- Evaluate and implement modern MLOps tools, frameworks, and best practices
- Develop technical documentation, architecture diagrams, and operational runbooks
- Mentor junior engineers and contribute to architecture reviews and technical planning
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:
- MLOps or ML platform engineering
- DevOps/DevSecOps supporting ML workloads
- Cloud infrastructure engineering for data/ML systems
- Experience with CI/CD tools (GitLab CI, Jenkins, GitHub Actions)
- Proficiency with Infrastructure-as-Code (Terraform, Ansible, or similar)
- Experience with Docker and Kubernetes
- Hands-on experience with AWS, Azure, or GCP (including GPU-based workloads)
- Strong understanding of the ML lifecycle (training ? deployment ? monitoring ? retraining)
- Scripting experience (Python, Bash, or PowerShell)
- Familiarity with security best practices in regulated environments
- Strong problem-solving, communication, and collaboration skills
Preferred Qualifications
- Master’s degree in a related field
- Experience with ML orchestration and tooling (Airflow, Kubeflow, MLflow, etc.)
- Experience with model registries, experiment tracking, and reproducibility frameworks
- Familiarity with RMF, STIGs, or other compliance frameworks
- Experience with observability tools (Prometheus, Grafana, ELK, etc.)
- Background supporting AI/ML systems in defense, intelligence, or high-assurance environments
- Relevant certifications (AWS DevOps Engineer, AWS ML Specialty, Kubernetes, etc.)
Why Join PSG?
At PSG, you’re not just taking a job—you’re enabling the future of AI in national security.
- Competitive compensation & benefits
- 9/80 flexible work schedule
- Professional development & tuition assistance
- Small, agile team with high ownership and impact
- Work on mission-critical AI/ML systems with real-world impact
- Opportunities to grow into technical leadership roles
Bring your MLOps expertise to PSG and help build secure, scalable, mission-driven AI systems that make a difference.
Salary Description
Salary range starts at $110,000, with the potential for higher compensation based on experience, skills, and mission needs.
group id: 10323967