Pay
$166K–$240K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 1,394 postings in the last year. Stated ranges, not salaries paid.
Cloud Infrastructure Engineer (AI/ML)
Cleveland, Ohio, United States of America
Open 3 months, first seen by us 108 days ago- Pay
- Pay not listedSimilar roles state $166K–$240K
- Work setting
- Not stated
- Employment
- Not stated
Before you apply
- Work authorization
- Must already have the right to work
We will not sponsor individuals for employment visas, now or in the future, for this job opening.


What you’ll work on
Full postingMigrate, optimize and support research workloads on AWS
Design, build and maintain MLOps pipelines for training, evaluation, deployment and monitoring
Develop prototypes and internal tools that speed up experimentation
Turn research objectives into scalable, documented engineering solutions
Mentor early-career engineers and share knowledge across teams
From the employer’s posting
Partner with DevOps and infrastructure teams to migrate, optimize, and support research workloads on AWS cloud platforms.
Design, build, and maintain machine learning operations (MLOps) pipelines that support model training, evaluation, deployment, and monitoring.
Develop prototypes and internal tools that accelerate experimentation, model development, and research workflows.
Translate research objectives into scalable, maintainable, and well-documented engineering solutions.
Provide technical guidance and mentorship to early-career engineers and support knowledge sharing across teams.
What you’ll bring
All qualificationsCore experience
- Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
- Experience working with AWS services such as:- Compute: EC2, ECS, EKS, Lambda
- Experience building and maintaining continuous integration and continuous deployment (CI/CD) systems, including tools such as GitHub Actions, GitLab CI, or Jenkins.
- Understanding of software engineering best practices, including:- Software design patterns
- Experience supporting research environments or collaborating closely with research teams.
- Ability to lead technical initiatives involving multiple stakeholders and cross-functional teams.
Preferred experience
- Experience with large-scale distributed computing frameworks such as Spark or Ray.
- Familiarity with data governance, compliance requirements, or regulated industries.
Qualification wording
Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
Experience working with AWS services such as:- Compute: EC2, ECS, EKS, Lambda
Experience building and maintaining continuous integration and continuous deployment (CI/CD) systems, including tools such as GitHub Actions, GitLab CI, or Jenkins.
Understanding of software engineering best practices, including:- Software design patterns
Experience supporting research environments or collaborating closely with research teams.
Ability to lead technical initiatives involving multiple stakeholders and cross-functional teams.
Experience with large-scale distributed computing frameworks such as Spark or Ray.
Familiarity with data governance, compliance requirements, or regulated industries.
Education & alternatives
Education & Experience - Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience. - 2 to 4 years of experience in DevOps, Site Reliability Engineering (SRE), cloud infrastructure, or related technical roles.
Posting record
Report an errorOpen 3 monthsWe first saw this posting 108 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jul 29, 2026108 days ago
- Recorded sightings
- 235
- Last seen by us
- Nov 13, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 108
Up longer than most. Similar jobs usually come down between day 8 and day 76.
Well past GE Healthcare’s usual: its jobs come down by about day 35.
From 5,460 similar postings that came down, and 49 of GE Healthcare’s. Coming down is not always a hire.
GE Healthcare is hiring
11 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring is picking up
- Takes jobs down at a usual pace
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- AWS
- Datadog
- Docker
- DynamoDB
- Kubernetes
- S3
- SageMaker
- Spark
- Terraform
Where the posting names them
Are you passionate about building reliable cloud infrastructure that helps researchers innovate faster? In this role, you will work at the intersection of cloud engineering, machine learning operations, and research computing, helping teams develop, test, and deploy cutting-edge solutions that advance MIM Research initiatives. You'll collaborate with researchers, engineers, and infrastructure partners to create scalable AWS-based environments, develop internal tools, and build engineering solutions that enable impactful research. We are looking for someone who enjoys solving complex problems, learning new technologies, and working in a collaborative, mission-driven environment. Job Description
In this role, you will: - Partner with DevOps and infrastructure teams to migrate, optimize, and support research workloads on AWS cloud platforms. - Design, build, and maintain machine learning operations (MLOps) pipelines that support model training, evaluation, deployment, and monitoring.
- 2 to 4 years of experience in DevOps, Site Reliability Engineering (SRE), cloud infrastructure, or related technical roles. - Experience supporting production systems within Amazon Web Services (AWS). Cloud & Infrastructure
Cloud & Infrastructure - Experience working with AWS services such as:- Compute: EC2, ECS, EKS, Lambda - Storage: S3, EFS
- Machine Learning: SageMaker (training, pipelines, and deployment) - Experience with Infrastructure as Code (IaC) tools such as Ansible, Terraform, CloudFormation, or AWS CDK. - Familiarity with containerization and orchestration technologies such as Docker, Docker Compose, and Kubernetes.
- CKAD - AWS Certified Solutions Architect – Associate - Or equivalent hands-on experience
- Strong foundation in Linux systems administration. - Experience with monitoring and observability practices using tools such as Prometheus, Datadog, or similar technologies. Programming & Software Engineering
- Experience with Infrastructure as Code (IaC) tools such as Ansible, Terraform, CloudFormation, or AWS CDK. - Familiarity with containerization and orchestration technologies such as Docker, Docker Compose, and Kubernetes. DevOps & Data Engineering
- Storage: S3, EFS - Data: DynamoDB - Machine Learning: SageMaker (training, pipelines, and deployment)
- Experience working with AWS services such as:- Compute: EC2, ECS, EKS, Lambda - Storage: S3, EFS - Data: DynamoDB
- Data: DynamoDB - Machine Learning: SageMaker (training, pipelines, and deployment) - Experience with Infrastructure as Code (IaC) tools such as Ansible, Terraform, CloudFormation, or AWS CDK.
While not required, the following experiences would be valuable: - Experience with large-scale distributed computing frameworks such as Spark or Ray. - Background in high-performance computing (HPC) or research computing environments.
Your next step
Complete your application on gehc.wd5.myworkdayjobs.com. The employer’s form will show what is required.
Applying through Phenom
- Phenom runs the employer’s careers site, but the application itself usually runs on another system, often Workday or Taleo. The advice for that system applies once you click Apply.
Already applied? Track this application
About GE Healthcare
- People
- About 54,000 in 2025, up 2% from the year before.Annual report (SEC Form 10-K)
- Company
- Listed as GEHC.
Demand for ML Engineer roles
New ML Engineer postings at the employers we follow are up 10% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
Job Description SummaryAre you passionate about building reliable cloud infrastructure that helps researchers innovate faster? In this role, you will work at the intersection of cloud engineering, machine learning operations, and research computing, helping teams develop, test, and deploy cutting-edge solutions that advance MIM Research initiatives.
You'll collaborate with researchers, engineers, and infrastructure partners to create scalable AWS-based environments, develop internal tools, and build engineering solutions that enable impactful research. We are looking for someone who enjoys solving complex problems, learning new technologies, and working in a collaborative, mission-driven environment.Job Description
You'll collaborate with researchers, engineers, and infrastructure partners to create scalable AWS-based environments, develop internal tools, and build engineering solutions that enable impactful research. We are looking for someone who enjoys solving complex problems, learning new technologies, and working in a collaborative, mission-driven environment.Job Description
Key Responsibilities
We will not sponsor individuals for employment visas, now or in the future, for this job opening.
In this role, you will:
- Partner with DevOps and infrastructure teams to migrate, optimize, and support research workloads on AWS cloud platforms.
- Design, build, and maintain machine learning operations (MLOps) pipelines that support model training, evaluation, deployment, and monitoring.
- Develop prototypes and internal tools that accelerate experimentation, model development, and research workflows.
- Translate research objectives into scalable, maintainable, and well-documented engineering solutions.
- Promote and support engineering best practices, including:
- Code quality, testing, and reliability
- Documentation and version control
- Data management and governance
- Experiment tracking and reproducibility
- Effectively manage multiple projects while balancing fast-paced research needs with long-term engineering sustainability.
- Provide technical guidance and mentorship to early-career engineers and support knowledge sharing across teams.
- Collaborate closely with research scientists, product teams, and infrastructure partners to deliver impactful solutions.
Education & Experience
- Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
- 2 to 4 years of experience in DevOps, Site Reliability Engineering (SRE), cloud infrastructure, or related technical roles.
- Experience supporting production systems within Amazon Web Services (AWS).
Cloud & Infrastructure
- Experience working with AWS services such as:
- Compute: EC2, ECS, EKS, Lambda
- Storage: S3, EFS
- Data: DynamoDB
- Machine Learning: SageMaker (training, pipelines, and deployment)
- Experience with Infrastructure as Code (IaC) tools such as Ansible, Terraform, CloudFormation, or AWS CDK.
- Familiarity with containerization and orchestration technologies such as Docker, Docker Compose, and Kubernetes.
DevOps & Data Engineering
- Experience building and maintaining continuous integration and continuous deployment (CI/CD) systems, including tools such as GitHub Actions, GitLab CI, or Jenkins.
- Strong foundation in Linux systems administration.
- Experience with monitoring and observability practices using tools such as Prometheus, Datadog, or similar technologies.
Programming & Software Engineering
- Understanding of software engineering best practices, including:
- Software design patterns
- API development (REST and gRPC)
- Testing methodologies and maintainable code architecture
Research & Applied Machine Learning
- Experience supporting research environments or collaborating closely with research teams.
- Ability to work effectively with evolving requirements, experimentation, and iterative development processes.
Collaboration & Leadership
- Ability to lead technical initiatives involving multiple stakeholders and cross-functional teams.
- Experience mentoring engineers and supporting the adoption of engineering best practices.
- Strong communication skills with the ability to connect technical concepts across research and engineering audiences.
While not required, the following experiences would be valuable:
- Experience with large-scale distributed computing frameworks such as Spark or Ray.
- Background in high-performance computing (HPC) or research computing environments.
- Familiarity with data governance, compliance requirements, or regulated industries.
- Contributions to open-source projects or published research.
- Relevant certifications such as:
- RHCSA or RHCE
- CKAD
- AWS Certified Solutions Architect – Associate
- Or equivalent hands-on experience
In this role, you will help create an environment where:
- Research teams can efficiently train, evaluate, and deploy machine learning models.
- Reliable and scalable infrastructure enables research teams to innovate with confidence.
- Best practices for reproducibility, testing, governance, and documentation are consistently adopted.
- Engineers at all levels receive mentorship and opportunities to grow.
- Projects are delivered effectively and aligned with organizational priorities.
- Research and engineering teams work together seamlessly to accelerate meaningful outcomes.
- Help build technology that empowers researchers and drives innovation.
- Work alongside collaborative teams of researchers, engineers, and technical leaders.
- Contribute to meaningful projects with real-world impact.
- Grow your technical expertise across cloud infrastructure, machine learning operations, and research computing.
- Share knowledge, mentor others, and continue developing your leadership skills in a supportive environment.
- Be part of a culture that values diverse perspectives, continuous learning, and inclusive collaboration.
#LI-CC1
GE HealthCare offers a great work environment, professional development, challenging careers, and competitive compensation. GE HealthCare is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.
GE HealthCare will only employ those who are legally authorized to work in the United States for this opening. Any offer of employment is conditioned upon the successful completion of a drug screen (as applicable).
While GE HealthCare does not currently require U.S. employees to be vaccinated against COVID-19, some GE HealthCare customers have vaccination mandates that may apply to certain GE HealthCare employees.
Relocation Assistance Provided: Yes
Source details
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Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Cleveland, Ohio, United States of America
Working pattern and location restrictions need checking in the full posting.
- Work authorization
GE HealthCare offers a great work environment, professional development, challenging careers, and competitive compensation. GE HealthCare is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law. GE HealthCare will only employ those who are legally authorized to work in the United States for this opening. Any offer of employment is conditioned upon the successful completion of a drug screen (as applicable). While GE HealthCare does not currently require U.S. employees to be vaccinated against COVID-19, some GE HealthCare customers have vaccination mandates that may apply to certain GE HealthCare employees.