1

Machine Learning Ops Engineer Jobs (NOW HIRING)

Summary The Machine Learning Ops Engineer I, under direct supervision, will assist in the development, deployment, and management of machine learning models, toolboxes and systems. This role involves ...

$93K - $149K/yr

The ML Ops Engineer II works in close collaboration with data scientists and various stakeholders across the hospital to develop solutions that improve patient care outcomes and operational ...

Keylent Inc is seeking a Machine Learning Ops Engineer to build and support a scalable and robust Machine Learning and Deep Learning platform for their data and analytics organization. The role ...

Keylent Inc is seeking a Machine Learning Ops Engineer to build and support a scalable and robust Machine Learning platform. The role involves working with data scientists and engineers to implement ...

Senior ML Ops Engineer

Philadelphia, PA · On-site

$99K - $137K/yr

As a Senior Machine Learning Ops Engineer, you will bridge Data Science and Engineering to develop AI-based features and ensure the reliability and scalability of machine learning models and services.

As the Machine Learning Ops Engineer for the AI Team you will: * Work closely with the Data Science team and the Data Engineers and DevOps teams in order to deploy machine learning models.

MLOps / AI Ops Engineer

Houston, TX · On-site

$50.25 - $69/hr

This role requires a strong background in machine learning operations and artificial intelligence ... Ops / Data Engineering / Software Engineering experience * Excellent communication is critical

New

Contract Experience: 10+ years in Software Engineering; 3+ years in AI/ML & Machine Learning Operations Job Overview Our client's Machine Learning AI team is seeking an experienced ML Ops Engineer to ...

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About ...

next page

Showing results 1-20

Machine Learning Ops Engineer information

See salary details

$31.5K

$128.8K

$193.5K

How much do machine learning ops engineer jobs pay per year?

As of Sep 4, 2026, the average yearly pay for machine learning ops engineer in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

What is a machine learning ops engineer?

A Machine Learning Ops Engineer (MLOps Engineer) focuses on deploying, monitoring, and maintaining machine learning models in production. They bridge the gap between data science and software engineering, ensuring models run efficiently, reliably, and at scale. Their responsibilities include automating workflows, managing infrastructure, and ensuring CI/CD pipelines for ML models. They work with tools like Kubernetes, Docker, and cloud platforms to streamline model deployment. Ultimately, an MLOps Engineer ensures that machine learning models are operationalized and continuously improved in a real-world environment.

What does a machine learning ops engineer do?

A typical day for a Machine Learning Ops Engineer involves collaborating with data scientists to streamline the deployment of models, building and maintaining scalable infrastructure on cloud services, and automating workflows with CI/CD tools. You may troubleshoot issues in production environments, monitor model performance, and implement solutions for model versioning and retraining. Often, you’ll work closely with software engineers, DevOps teams, and data analysts to ensure seamless integration of machine learning solutions into products. This cross-functional role keeps you engaged with cutting-edge technology and provides opportunities to influence both technical and business outcomes.

What skills and qualifications are needed to be a machine learning ops engineer?

To thrive as a Machine Learning Ops Engineer, you need a solid grasp of machine learning concepts, cloud platforms, software engineering, and DevOps practices, typically supported by a degree in computer science or a related field. Experience with tools like Docker, Kubernetes, TensorFlow, CI/CD pipelines, and certifications such as AWS Certified Machine Learning – Specialty are highly valuable. Strong problem-solving skills, communication, and the ability to work collaboratively across data science and engineering teams set top candidates apart. These skills ensure reliable deployment, scalability, and optimization of machine learning models in production environments.

Are machine learning ops engineers in demand?

Machine Learning Ops Engineers are in high demand due to the increasing adoption of AI and machine learning across industries. They are needed to develop, deploy, and maintain scalable ML systems, often requiring skills in cloud platforms, automation, and tools like Kubernetes and TensorFlow. The role is expected to grow as organizations prioritize AI-driven solutions and infrastructure automation.
More about Machine Learning Ops Engineer jobs

What cities are hiring for Machine Learning Ops Engineer jobs?

Cities with the most Machine Learning Ops Engineer job openings:

What are the most commonly searched types of Machine Learning Ops Engineer jobs?

The most popular types of Machine Learning Ops Engineer jobs are:

What states have the most Machine Learning Ops Engineer jobs?

States with the most job openings for Machine Learning Ops Engineer jobs include:

Infographic showing various Machine Learning Ops Engineer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 24% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.

Engineer I, Machine Learning Ops CBM Lab

Shirley Ryan AbilityLab

Chicago, IL • On-site

$60 - $99.70/hr

Other

Re-posted 10 days ago


Shirley Ryan AbilityLab rating

7.1

Company rating: 7.1 out of 10

Based on 14 frontline employees who took The Breakroom Quiz


Job description

## Engineer I, Machine Learning Ops CBM LabApplylocations: Chicago, ILtime type: Full timeposted on: Posted Todayjob requisition id: JR-1065210Shirley Ryan AbilityLab is the global leader in physical medicine and rehabilitation for adults and children with the most severe, complex conditions. By joining our team, you’ll be part of our life-changing mission and vision. You’ll contribute to an innovative, multifaceted culture that is second to none — one that embraces collaboration, excellence, discovery and compassion. You’ll play a role in something that’s never been done before as we integrate science and clinical care to help patients achieve better, faster outcomes — as we Advance Human Ability, together.## ## **Job Description Summary**The Machine Learning Ops Engineer I, under direct supervision, will assist in the development, deployment, and management of machine learning models, toolboxes and systems. This role involves collaborating with data scientists and software engineers to facilitate the implementation of artificial intelligence (AI) and machine learning (ML) solutions in production environments. The Machine Learning Ops Engineer I will consistently demonstrate support of the Shirley Ryan AbilityLab statement of Vision, Mission and Core Values by striving for excellence, contributing to the team efforts and showing respect and compassion for patients and their families, fellow employees, and all others with whom there is contact at or in the interest of the institute. The Machine Learning Ops Engineer I will demonstrate Shirley Ryan AbilityLab Core Attributes: Communication, Accountability, Flexibility/Adaptability, Judgment/Problem Solving, Customer Service and Core Values (Hope, Compassion, Discovery, Collaboration, and Commitment to Excellence) while fulfilling job duties.## ## **Job Description****The Machine Learning Ops will:*** Participate in a team to deploy and monitor machine learning models, ensuring their stability and reliability.* Review, organize and curate data as directed. Implements and tests machine learning algorithms as directed.* Assist in the development and maintenance of continuous integration and delivery pipelines for machine learning systems.* Contribute to the automation of model training and deployment processes.* Assist with the management of machine learning infrastructure and resources.* Support the team in implementing best practices for machine learning operations.* Help in troubleshooting and resolving issues in deployed machine learning models.* Participate in maintaining a safe and secure computing environment in compliance with organizational policies and procedures.* Participate in maintaining a safe work environment through adherence to policies and procedures relative to safety, fire prevention, hazard communications, security, equipment use and maintenance, infection control and vehicle safety.* Perform all other duties that may be assigned in the best interest of the Shirley Ryan AbilityLab.**Reporting Relationships:*** Reports directly to a designated engineering manager.**Knowledge, Skills & Abilities Required:*** A foundational level of knowledge in computer science, engineering, data science, or related field, generally acquired through the completion of a Bachelor’s Degree.* Basic understanding of machine learning concepts and workflows.* Familiarity with version control systems, preferably Git, is required.* Basic understanding of Git commands and workflows (e.g., commit, push, pull, merge, branch) is expected.* Familiarity with programming languages like Python and tools like TensorFlow or PyTorch.* Ability to work under supervision on assigned tasks.* Good communication skills and the ability to work well in a collaborative environment.* Entry level position with no previous professional experience.* Learns to use professional concepts while working on projects of limited scope.* Normally receives detailed instructions on all work.* Able to take direction and complete defined tasks in support of engineering team.* Able to apply institute policies and procedures to resolve routine issues.* Able to follow standard practices and procedures in analyzing situations or data from which answers can be readily obtained.* Able to build stable working relationships with multidisciplinary team.**Working Conditions*** Normal office environment with little or no exposure to dust or extreme temperature.The above statements are intended to describe the general nature and level of work being performed by people assigned to this classification. They are not intended to be construed as an exhaustive list of all responsibilities, duties and skills required of personnel so classified.**Pay and Benefits\*:****Pay Range:**$60,000.00 - $99,700.00## **Benefits:**Shirley Ryan AbilityLab offers a comprehensive benefits program that is competitive with our industry peers in our geographic locations: https://www.sralab.org/benefits*\*Benefits and benefits’ eligibility can vary by position. Actual compensation will be determined by equity and qualifications of the role.* #J-18808-Ljbffr

What Shirley Ryan AbilityLab employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom