ML OPS AI ENGINEER II

Openkyber; Atlanta (GA); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Medical, Vision, Dental Insurance

Life and Disability Insurance

401(k) plan

Job summary

Openkyber, LLC is seeking an ML Ops AI Engineer II to support the delivery of machine learning solutions from development through live production in Coppell, Texas. This long-term contract role focuses on strengthening ML infrastructure, improving deployment reliability, and partnering with AI teams to operationalize models at scale.

The role emphasizes building repeatable systems, expanding observability, and maintaining efficient, stable, and cost-conscious model workflows across cloud

Qualifications

• 3 to 5 years of experience in MLOps, machine learning platform engineering, or AI infrastructure roles.
• Hands-on experience with Azure and managing compute resources for model training and inference.
• Background in containerization and orchestration technologies, including Docker and Kubernetes.
• Experience building CI/CD pipelines for ML or software delivery workflows.
• Proficiency in Python, automation, and infrastructure-as-code practices.
• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical discipline.

Responsibilities

• Lead the end-to-end operationalization of machine learning models, moving solutions from experimentation into production environments.
• Develop and support ML infrastructure, automated pipelines, and deployment frameworks to improve reliability.
• Create and manage containerized workloads using Docker and coordinate production services through Kubernetes.
• Establish and maintain CI/CD processes for model training, packaging, testing, and release management.
• Implement tools and standards for experiment tracking, feature lineage, and model version control.

Skills

Python

Automation

Agile collaboration

Education

Bachelor's or Master's in CS/Engineering

Tools

Docker

Kubernetes

CI/CD tools

Terraform (IaC)

Job description

Description We are looking for an ML OPS AI Engineer II to support the delivery of machine learning solutions from development through live production in Coppell, Texas. This Long-term Contract opportunity is ideal for a hands-on engineer who can strengthen ML infrastructure, improve deployment reliability, and partner closely with AI teams to operationalize models at scale.

The role focuses on building repeatable systems, increasing observability, and ensuring model workflows remain efficient, stable, and cost-conscious across cloud-based environments.

Responsibilities

• Lead the end-to-end operationalization of machine learning models, moving solutions from experimentation into dependable production environments.
• Develop and support ML infrastructure, automated pipelines, and deployment frameworks that improve reliability and reduce manual effort.
• Create and manage containerized workloads using Docker and coordinate production services through Kubernetes.
• Establish and maintain CI/CD processes for model training, packaging, testing, and release management.
• Implement tools and standards for experiment tracking, feature lineage, and model version control to enable reproducibility.
• Build monitoring solutions that surface system health, model behavior, and data drift, helping teams respond quickly to production issues.
• Provision and optimize cloud and compute resources to support both training and inference workloads effectively.
• Improve scalability, operational visibility, and cost efficiency across deployed AI services.
• Partner with data scientists and ML engineers to simplify deployment pathways and align platform capabilities with model development needs.

Requirements

3 to 5 years of experience in MLOps, machine learning platform engineering, or AI infrastructure roles. Demonstrated success deploying, maintaining, and improving machine learning models in production settings. Hands-on experience with Azure and managing compute resources for model training and inference. Strong background in containerization and orchestration technologies, including Docker and Kubernetes. Practical experience building CI/CD pipelines for machine learning or broader software delivery workflows. Proficiency in Python, along with experience in automation and infrastructure-as-code practices. Bachelor's or Master's degree in Computer Science, Engineering, or a related technical discipline. Working knowledge of AI/ML concepts, with the ability to collaborate effectively in a fast-paced, agile environment.

All applicants applying for U.S. job openings must be legally authorized to work in the United States.

Benefits are available to contract/temporary professionals, including medical, vision, dental, and life and disability insurance.

Hired contract/temporary professionals are also eligible to enroll in our company 401(k) plan.

An Equal Opportunity Employer. M/F/Disability/Veterans.

OpenKyber.gobenefits.net for more information.