Remote AI Systems Engineer, ML Ops & Infra

ARA; Albuquerque (NM); Hybrid; USD 105,000 - 165,000; Full time

Job summary

ARA is seeking an experienced engineer to lead deployment and ongoing support of enterprise AI platforms. You will design scalable AI infrastructure, operationalize ML workflows, and build robust CI/CD/MLOps pipelines across hybrid and cloud environments.

Ideal candidates bring 8–10 years of engineering experience, strong Python/Bash skills, familiarity with PyTorch and Hugging Face, and a solid grasp of security standards such as NIST/CMMC. Collaboration across divisions is essential.

Qualifications

• Bachelor’s degree in a STEM field.
• 2+ years supporting AI/ML platforms, MLOps workflows, or AI-enabled infra.
• Strong coding and automation in Python or Bash.
• Experience with PyTorch, Hugging Face, or similar ecosystems.
• Proficiency with CI/CD, containerization, and Kubernetes.
• Experience deploying AI/ML models into operational environments.
• Familiarity with NIST/CMMC security frameworks.
• Knowledge of OAuth in enterprise environments.
• Excellent collaboration across technical and non-technical teams.

Responsibilities

• Lead deployment, integration, and support of AI platforms and services.
• Design, implement, and optimize AI infrastructure with server, cloud, and platform teams.
• Operationalize ML workflows from development to production.
• Build and maintain CI/CD and MLOps pipelines for model packaging, testing, deployment, and lifecycle management.
• Automate infrastructure using scripting and IaC; ensure security and governance.

Skills

Python scripting

Shell scripting

Strong communication

Team collaboration

Security/compliance awareness

Education

Bachelor’s degree in CS/Engineering or related field

Tools

PyTorch

Hugging Face

CI/CD pipelines

Git workflows

Docker/Kubernetes

Job description

ARA is seeking an experienced engineer to lead deployment and ongoing support of enterprise AI platforms. You will design scalable AI infrastructure, operationalize ML workflows, and build robust CI/CD/MLOps pipelines across hybrid and cloud environments.

Ideal candidates bring 8–10 years of engineering experience, strong Python/Bash skills, familiarity with PyTorch and Hugging Face, and a solid grasp of security standards such as NIST/CMMC. Collaboration across divisions is essential.