ZipRecruiter

Log In

1

Mlops Data Engineer Jobs in Chicago, IL (NOW HIRING)

Alpha Consulting Corp.

Data Engineer

Chicago, IL · On-site

$118K - $141K/yr

Alpha Consulting Corp. is seeking a highly skilled MLOps Engineer / Python Developer with expertise in building and maintaining scalable data and machine learning pipelines. The role involves ...

1872 Consulting

Remote Data Engineer

Oak Brook, IL · Remote

$115K - $138K/yr

Sr. Data Engineer This role is responsible for providing technical expertise and leadership to ... Machine Learning Operationalization (MLOps) proficiency. * Proficiency with streaming design ...

1872 Consulting

Remote Data Engineer

Oak Brook, IL · Remote

$115K - $138K/yr

Sr. Data Engineer This role is responsible for providing technical expertise and leadership to ... Machine Learning Operationalization (MLOps) proficiency. * Proficiency with streaming design ...

Accord Technologies Inc.

MLOPS Engineer

Chicago, IL · On-site

MLOPS Engineer Location: Chicago, IL Duration: 12+ months Position type: W2 contract Required Skills f or the MLOps Engineer: - Bachelor's plus 9+ years of experience, Master ...

Permute AI, Inc

Senior Data Engineer

Chicago, IL · On-site

$180K - $280K/yr

Senior Data Engineer - AI Systems Employment Type: Full-time Company: Permute (www.permute.ai ... Data infrastructure supporting ML training, MLOps, evaluation, and deployment * Data quality ...

Bank of America

Data Engineer - Python/AI

Addison, IL · On-site

$114K - $137K/yr

Identifies, defines, and documents data engineering requirements, communicating required ... Proven experience productionizing ML models using MLflow and enterprisegrade MLOps frameworks

Grindr

Senior Staff MLOps Engineer

Chicago, IL · On-site

$190K - $315K/yr

As a Staff MLOps Engineer, you will build and own the infrastructure, tooling, and scalable systems ... You'll architect and maintain the platforms that power data ingestion, feature computation, model ...

Huntington

MLOps Automation Senior Lead Engineer

Chicago, IL · On-site +1

$107K - $140K/yr

The MLOps Automation Engineering Senior Lead will lead a team responsible for building and ... Streamline the data, analytics, and model development lifecycle by identifying pain points and ...

Socket.dev

Data Engineering Lead (Hybrid)

Chicago, IL · On-site

$190 - $220/hr

Familiarity with data science workflows, ML model lifecycle, and MLOps concepts * Expertise in data engineering -- including model design, testing strategy, incremental patterns, and layer boundary ...

next page

Showing results 1-20

All JobsMlops Data Engineer JobsMlops Data Engineer Jobs in Chicago, IL

Mlops Data Engineer information

See Chicago, IL salary details

$45.8K

$133.6K

$182.9K

How much do mlops data engineer jobs pay per year?

As of Sep 6, 2026, the average yearly pay for mlops data engineer in Chicago, IL is $133,627.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,000.00 and $141,600.00 per year, depending on experience, location, and employer.

What is an MLOps data engineer?

MLOps Data Engineers are professionals who blend expertise in machine learning (ML), operations (Ops), and data engineering to streamline the deployment and management of ML models in production environments. They design and maintain data pipelines, automate workflows, and ensure the scalability, reliability, and reproducibility of machine learning systems. Their role bridges the gap between data scientists and IT operations, enabling seamless integration of ML models into real-world applications.

What are the key skills and qualifications needed to thrive as an MLOps data engineer?

To thrive as an MLOps Data Engineer, you need a strong background in data engineering, machine learning workflows, and software development, usually supported by a degree in computer science or a related field. Expertise with cloud platforms (such as AWS, GCP, or Azure), CI/CD pipelines, containerization tools (like Docker and Kubernetes), and familiarity with orchestration frameworks are typically required, along with certifications in cloud or data engineering. Strong problem-solving abilities, collaboration, and clear communication set professionals apart in this role. These skills and qualities are critical to efficiently deploying scalable machine learning solutions and ensuring smooth collaboration between data science and engineering teams.

What are some common challenges MLOps data engineers face when deploying machine learning models into production?

MLOps Data Engineers often encounter challenges such as ensuring seamless integration between data pipelines and model serving infrastructure, managing consistent data quality, and automating model retraining and monitoring. Another common hurdle is maintaining scalability and reliability as data volumes grow, and efficiently collaborating with data scientists, software engineers, and DevOps teams. Addressing these challenges requires strong communication skills, familiarity with cloud platforms, and a proactive approach to troubleshooting and automation.

What is the difference between Mlops Data Engineer vs Data Scientist?

AspectMlops Data EngineerData Scientist
Required SkillsMachine learning deployment, cloud platforms, scripting, data pipelinesStatistical analysis, programming, data visualization, machine learning modeling
CertificationsCloud certifications, ML engineering coursesData science certifications, statistical courses
Work EnvironmentData pipelines, cloud infrastructure, ML deployment systemsData analysis, modeling, research environments
Industry UsageTech companies, AI-focused firms, cloud service providersResearch institutions, analytics firms, tech companies

The main difference between an Mlops Data Engineer and a Data Scientist lies in their focus areas. Mlops Data Engineers specialize in deploying, maintaining, and scaling machine learning models within production environments, emphasizing infrastructure and automation. Data Scientists primarily focus on analyzing data, building models, and deriving insights. Both roles require strong technical skills, but their day-to-day tasks and career paths differ significantly.

Are MLOps Data Engineers in demand?

MLOps Data Engineers are in high demand due to the increasing adoption of machine learning and AI across industries. They are skilled in deploying, managing, and maintaining ML models using tools like Docker, Kubernetes, and cloud platforms, making their expertise highly sought after in data-driven organizations.

Is MLOps required for data engineers?

MLOps is increasingly important for data engineers involved in deploying and maintaining machine learning models, as it encompasses practices like automation, monitoring, and version control. While not always mandatory, knowledge of MLOps tools such as Docker, Kubernetes, and CI/CD pipelines enhances a data engineer's ability to support scalable and reliable ML systems.

What are popular job titles related to Mlops Data Engineer jobs in Chicago, IL?

For Mlops Data Engineer jobs in Chicago, IL, the most frequently searched job titles are:

What job categories do people searching Mlops Data Engineer jobs in Chicago, IL look for?

The top searched job categories for Mlops Data Engineer jobs in Chicago, IL are:

What cities near Chicago, IL are hiring for Mlops Data Engineer jobs?

Cities near Chicago, IL with the most Mlops Data Engineer job openings:

Mlops Data Engineer jobs near you
Infographic showing various Mlops Data Engineer job openings in Chicago, IL as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $133,627 per year, or $64.2 per hour.

Mid Level MLOps Engineer/Remote EST/CST

Motion Recruitment Partners, LLC

Chicago, IL • On-site

Other

Medical, Dental, Vision, PTO

Posted 8 days ago

Job description

Our client is a global performance marketing organization operating at the intersection of brand marketing, technology, and analytics, helping businesses design and manage data-driven marketing and brand strategies. They are hiring for a Mid-Level AI/ML Ops Engineer to build and maintain the infrastructure, deployment pipelines, monitoring, and cloud systems that gets AI and machine learning models into production reliably, securely, and at scale.
This is a hands-on opportunity to own the operational backbone of a growing AI practice, working side by side with AI Engineers and the AI Tech Lead rather than setting architecture in isolation. You will take deployment and infrastructure requirements and turn them into dependable, monitored production systems, all while deepening your expertise across MLOps, cloud AI platforms, and LLM deployment. It is a great fit for someone who is detail oriented and reliability focused, stays calm and methodical when production issues come up, and wants room to grow into a stronger voice on the operational side of AI/ML.
Required Skills & Experience
  • Bachelor's degree in Computer Science, Engineering, or a related field, or comparable experience
  • 3-5 years of experience in DevOps, MLOps, data engineering, or a related infrastructure/operations role
  • Hands-on experience deploying machine learning models into production environments
  • Working knowledge of Databricks and cloud AI platforms (AWS preferred, including familiarity with services like Bedrock)
  • Experience with containerization and orchestration tools (Docker, Kubernetes or equivalent)
  • Proficiency in Python and familiarity with CI/CD tooling
  • Experience with monitoring and observability tooling for production systems
  • Solid understanding of data analytics fundamentals
Desired Skills & Experience
  • Familiarity with LLM deployment considerations (latency, cost, versioning)
  • Experience with SQL
What You Will Be Doing
Tech Breakdown
  • Databricks and AWS cloud AI platforms, including Bedrock
  • Docker and Kubernetes (or equivalent orchestration)
  • Python and CI/CD tooling
  • Monitoring and observability platforms
Daily Responsibilities
  • Build and maintain CI/CD pipelines for deploying AI/ML models into production
  • Implement monitoring and observability to catch performance degradation, drift, and failures early
  • Manage cloud infrastructure supporting AI workloads, including containerized services and cloud AI platforms
  • Collaborate with AI Engineers and the AI Tech Lead to translate requirements into deployment plans
  • Troubleshoot production issues and support model versioning, reproducibility, and rollback processes
  • Monitor and optimize the cost and resource efficiency of AI/ML workloads, flagging operational risks before they become incidents

The Offer
  • Bonus eligible
You will receive the following benefits:
  • Medical, Dental, and Vision Insurance
  • Vacation Time
  • Stock Options

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

Apply