The ideal candidate brings strong experience in automation, Kubernetes-based deployments, and modern MLOps practices, along with the ability to translate technical needs into durable operational ...
Quick apply
The ideal candidate brings strong experience in automation, Kubernetes-based deployments, and modern MLOps practices, along with the ability to translate technical needs into durable operational ...
Quick apply
The ideal candidate brings strong experience in automation, Kubernetes-based deployments, and modern MLOps practices, along with the ability to translate technical needs into durable operational ...
Albuquerque, NM · On-site +1
$95K - $130K/yr
Build and maintain CI/CD and MLOps pipelines for model packaging, testing, deployment, rollback, and lifecycle management. * Implement infrastructure automation using scripting, Infrastructure as ...
Albuquerque, NM · On-site +1
$95K - $130K/yr
Build and maintain CI/CD and MLOps pipelines for model packaging, testing, deployment, rollback, and lifecycle management. * Implement infrastructure automation using scripting, Infrastructure as ...
Kirtland Air Force Base, NM · On-site
$110K - $150K/yr
Software Development and Program Integration: • Lead and mentor software development teams, establishing technical standards, MLOps practices, and development workflows while directing the ...
Kirtland Air Force Base, NM · On-site
$110K - $150K/yr
Software Development and Program Integration: • Lead and mentor software development teams, establishing technical standards, MLOps practices, and development workflows while directing the ...
Software Development and Program Integration: · Lead and mentor software development teams, establishing technical standards, MLOps practices, and development workflows while directing the ...
Software Development and Program Integration: · Lead and mentor software development teams, establishing technical standards, MLOps practices, and development workflows while directing the ...
Knowledge of MLOps practices for deploying and maintaining AI solutions. * Previous experience in automation or workflow optimization projects. Benefits Why Join Us? * Work with cutting-edge ...
Knowledge of MLOps practices for deploying and maintaining AI solutions. * Previous experience in automation or workflow optimization projects. Benefits Why Join Us? * Work with cutting-edge ...
Albuquerque, NM · Hybrid
$61.75 - $79.50/hr
Define and govern enterprise AI architecture standards , including model lifecycle management, MLOps, and AI platform integration. * Ensure responsible and compliant AI adoption, aligned with AI ...
Albuquerque, NM · Hybrid
$61.75 - $79.50/hr
Define and govern enterprise AI architecture standards , including model lifecycle management, MLOps, and AI platform integration. * Ensure responsible and compliant AI adoption, aligned with AI ...
Albuquerque, NM · On-site +1
Familiarity with modern MLOps tooling and practices, including containers, workflow orchestration, deployment patterns, telemetry, and experimentation systems * Strong Python programming skills and ...
Albuquerque, NM · On-site +1
Familiarity with modern MLOps tooling and practices, including containers, workflow orchestration, deployment patterns, telemetry, and experimentation systems * Strong Python programming skills and ...
| Aspect | Mlops | Data Engineer |
|---|---|---|
| Primary Focus | Deploying, managing, and monitoring machine learning models in production | Building and maintaining data pipelines and infrastructure for data processing |
| Skills & Certifications | Machine learning, DevOps, cloud platforms, scripting | SQL, ETL, data warehousing, programming |
| Work Environment | Collaborates with data scientists, software engineers, and DevOps teams | Works with data analysts, data scientists, and software developers |
| Industry Usage | AI/ML projects, production environments, cloud services | Data infrastructure, analytics, big data processing |
While both Mlops and Data Engineers work closely with data and cloud technologies, Mlops specialists focus on deploying and maintaining machine learning models in production, ensuring their scalability and reliability. Data Engineers primarily build data pipelines and infrastructure to support data analysis and ML workflows. Understanding these distinctions helps organizations assign the right roles for their AI and data projects.
Full-time
Posted 20 days ago
We are looking for an Artificial Intelligence (AI) Engineer to support the design, deployment, and ongoing operation of AI systems for a government services organization in Albuquerque, New Mexico. This position centers on building reliable AI infrastructure, enabling machine learning solutions in production, and partnering with cross-functional teams to deliver secure, scalable platforms.
The ideal candidate brings strong experience in automation, Kubernetes-based deployments, and modern MLOps practices, along with the ability to translate technical needs into durable operational solutions.
Responsibilities:
• Direct the rollout and integration of AI platforms and services, ensuring they work effectively with existing enterprise technologies and operational standards.
• Architect, implement, and refine AI infrastructure in partnership with cloud, server, and platform engineering teams to support dependable system performance.
• Move machine learning solutions from development into production by establishing repeatable processes for deployment, maintenance, and long-term support.
• Create and manage CI/CD and MLOps workflows that cover model validation, packaging, release, rollback, and lifecycle oversight.
• Automate infrastructure and platform operations through scripting, infrastructure-as-code methods, and configuration management tools.
• Troubleshoot platform and service issues, perform root cause analysis, and produce clear technical documentation for support and maintenance activities.
• Strengthen system visibility by implementing logging, monitoring, alerting, and incident response practices across AI environments.
• Uphold security and compliance expectations by contributing to audits, remediation efforts, vulnerability management, and secure design reviews.
• Identify and deliver improvements that increase performance, scalability, reliability, and cost efficiency across AI-enabled systems.
• Work with technical and business stakeholders to align AI implementations with organizational priorities and evaluate emerging tools for long-term operational value.
Other duties as needed
Interviews are currently being conducted, for immediate consideration please apply.
This position requires some onsite in Albuquerque, New Mexico with a preferred Hybrid work schedule.
• Bachelor’s degree in computer science, software engineering, information technology, or a related technical field, or equivalent practical experience.
• Must have experience deploying Kubernetes and MCP servers integrated with AI data sources.
• At least 2 years of hands-on experience supporting AI or machine learning platforms, model deployment, MLOps processes, or AI-focused infrastructure.
• Demonstrated experience deploying and managing server-based workloads in Kubernetes environments.
• Strong programming and automation capabilities using Python, Bash, or similar scripting languages.
• Solid understanding of DevOps and MLOps practices, including Git-based development, CI/CD pipelines, containers, and Kubernetes orchestration.
• Experience working with AI and machine learning frameworks such as PyTorch, Hugging Face, or related ecosystems.
• Familiarity with enterprise security and compliance requirements, including authentication approaches such as OAuth and regulated operating environments.
• Ability to communicate effectively with both technical and non-technical teams and collaborate across multiple functions.
• Secret Security Clearance – Active or Inactive or ability to get a clearance.
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