Mid-Level MLOps Engineer | AWS, Kubernetes, CI/CD

Motion Recruitment; Chicago (IL); Hybrid; USD 90,000 - 130,000; Full time

Benefits offered by this job

Medical, Dental, and Vision Insurance

401(k) Program

Paid Vacation & Holidays

Professional Development Opportunities

Life Insurance

Employee Assistance Programs

Flexible Work Environment

Job summary

Motion Recruitment Partners LLC is seeking a Mid-Level AI/ML Ops Engineer to scale AI initiatives using AWS, Databricks, Docker, Kubernetes, and CI/CD pipelines. This role emphasizes production-grade deployments and platform reliability.

You will work on deploying ML models to production, improving monitoring and automation, and collaborating with cross-functional teams to support mission-critical AI systems.

Qualifications

• 3–5 years in MLOps/DevOps/Platform engineering or similar roles.
• Experience deploying ML models to production environments.
• Strong knowledge of AWS cloud services.
• Experience with Databricks and container platforms.
• Hands-on with Docker and Kubernetes.
• Proficiency in Python and CI/CD pipelines.
• Familiarity with monitoring and observability tools.
• Experience supporting production environments and troubleshooting incidents.

Responsibilities

• Hands-on engineering across cloud infrastructure, containers, and CI/CD.
• Collaborate with teams to deploy and monitor ML workloads in production.
• Maintain and improve reliability, observability, and automation.
• Support incident response and operational excellence in ML systems.

Skills

MLOps

DevOps

Python

CI/CD

Monitoring

Education

Bachelor's degree in CS/Engineering

Tools

Docker

Kubernetes

AWS

Databricks

Job description

An innovative data-driven marketing and technology organization is seeking a Mid-Level AI/ML Ops Engineer to help support and scale AI initiatives across the business. This full-time opportunity offers the chance to work with modern cloud technologies including AWS, Databricks, Docker, Kubernetes, CI/CD pipelines, and AI-powered platforms while helping deploy machine learning solutions into secure and reliable production environments.

This is an excellent opportunity for an operations-minded engineer who enjoys solving production challenges and improving platform reliability. The organization has built a strong reputation for investing in employee development, fostering collaboration, and creating an environment where engineers can deepen their expertise in AI infrastructure, cloud platforms, and MLOps best practices. You'll have direct exposure to cutting-edge AI projects and the opportunity to help shape operational standards as AI adoption continues to grow.Required Skills & Experience

• 3-5 years of experience in MLOps, DevOps, Cloud Engineering, Platform Engineering, or similar roles
• Experience deploying machine learning models into production environments
• Strong knowledge of AWS cloud services
• Experience with Databricks
• Hands-on experience with Docker and Kubernetes
• Proficiency in Python
• Experience building and maintaining CI/CD pipelines
• Familiarity with monitoring and observability platforms
• Experience supporting production environments and troubleshooting incidents
• Bachelor's degree in Computer Science, Engineering, or equivalent experience

Desired Skills & Experience

• Experience with AWS Bedrock, SageMaker, or other AI platforms
• Exposure to large language model deployment and optimization
• Knowledge of model monitoring and drift detection
• SQL and data analytics experience
• Infrastructure as Code experience
• Experience supporting highly scalable cloud applications

What You Will Be Doing Tech Breakdown

• 40% AWS Cloud Infrastructure
• 25% Kubernetes & Container Platforms
• 20% CI/CD & Automation
• 15% Monitoring, Observability & Support

Daily Responsibilities

• 75% Hands-On Engineering
• 5% Management Duties
• 20% Team Collaboration

The Offer

• Bonus Eligible

You will receive the following benefits:

• Medical, Dental, and Vision Insurance
• 401(k) Program
• Paid Vacation & Holidays
• Professional Development Opportunities
• Life Insurance
• Employee Assistance Programs
• Flexible Work Environment

Applicants must be currently authorized to work in the United States on a full-time basis now and in the future.

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