Lead MLOps Engineer

Stem IT; Denver (CO); Remote; USD 180,000 - 260,000; Full time

Benefits offered by this job

Fully remote

Annual bonus

401(k) with employer match

Generous PTO

Continuing education and professional

Ownership and visibility in AI init

Job summary

Stem IT is seeking a Lead MLOps Engineer in a fully remote role with Denver-area coordination. You will guide a small engineering team to design and deploy production-grade ML systems, establish robust MLOps practices, and mentor engineers across the organization.

The role spans ML, LLMs, cloud infra, and shaping the technical roadmap for a new AI platform. The ideal candidate has strong ML deployment experience, expertise in Python, and familiarity with cloud ML services.

Qualifications

• Strong experience developing and deploying machine learning systems.
• Proficiency in Python.
• Experience with TensorFlow, PyTorch, or similar ML frameworks.
• Hands-on experience with cloud-based ML/AI platforms, including AWS, Azure, and/or GCP.
• Experience building and deploying MLOps processes and production ML systems.
• Experience with modern AI services such as Amazon SageMaker, Bedrock, Hugging Face, or comparable platforms.
• Strong understanding of machine learning architecture, model development, deployment, and monitoring.
• Ability to evaluate emerging AI technologies and determine their practical application to real-world problems.

Responsibilities

• Lead a small team of engineers and set technical direction.
• Evaluate emerging AI technologies and determine practical applications.
• Architect and deploy production-grade ML systems across platforms.
• Establish MLOps practices and governance for scalable operations.
• Mentor engineers across the organization to raise technical capability.

Skills

ML system development

Python

MLOps

Cloud platforms (AWS/Azure/GCP)

LLMs & Generative AI

Team leadership

Terraform / IaC

AI platform development

Regulated environments experience

Production ML deployment

Job description

Mission Driven digital transformation firm in Denver, Colorado (full-remote option) is looking to add a Lead MLOps Engineer to its growing engineering team. This person will lead a small team, responsible for: evaluating emerging AI technologies, architecting and deploying production grade machine learning systems, establish MLOps practices, and mentor engineers across the organization.

This is a highly technical role for someone who enjoys building from the ground up and have the opportunity to work across machine learning, LLMs, cloud infrastructure, and production engineering while helping define the technical roadmap for a brand-new AI platform.

Preferred Qualifications:

• Strong professional experience developing and deploying machine learning systems
• Proficiency in Python
• Experience with TensorFlow, PyTorch, or similar ML frameworks
• Hands-on experience with cloud-based ML/AI platforms, including AWS, Azure, and/or GCP
• Experience building and deploying MLOps processes and production ML systems
• Experience with modern AI services such as Amazon SageMaker, Bedrock, Hugging Face, or comparable platforms
• Strong understanding of machine learning architecture, model development, deployment, and monitoring
• Ability to evaluate emerging AI technologies and determine their practical application to real-world problems
• Demonstrated ability to provide technical leadership and mentor other engineers

Strong Plus:

• Experience working with LLMs and Generative AI
• Experience with Terraform, AWS CDK, or other infrastructure-as-code technologies
• Experience building AI/ML platforms from the ground up
• Experience leading or mentoring engineering teams
• Experience working with federal government or regulated environments
• Experience taking AI/ML solutions from experimentation and prototyping into production

Package:

• Fully remote
• Competitive base compensation
• Annual bonus opportunities
• 401(k) with employer match
• Generous PTO
• Continuing education and professional development support
• Significant ownership and visibility within a new AI initiative