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Medical Machine Learning Jobs in Georgia (NOW HIRING)

Whiterabbit.ai

Learn and understand a large body of research in deep learning and machine learning * Participate in cutting-edge research for medical applications of computer vision Must Have Experience

Wipro Limited

AI ENGINEER

Louisville, GA · On-site

$45K - $110K/yr

Do Research, design, develop, and modify computer vision and machine learning. algorithms and ... of medical and dental benefits options, disability insurance, paid time off (inclusive of sick ...

Whiterabbit.ai

Learn and understand a large body of research in deep learning and machine learning * Participate in cutting-edge research for medical applications of computer vision Must Have Experience

Whiterabbit.ai

Learn and understand a large body of research in deep learning and machine learning * Participate in cutting-edge research for medical applications of computer vision Must Have Experience

Coreandmain

Machine Operator

Willacoochee, GA · On-site

$13.75 - $16.25/hr

You are energized when learning about new products and machinery. ARE power tools and machine ... Medical with 100% preventative care coverage * Health Savings Account * Dental and Vision * 401K

Whiterabbit.ai

Learn and understand a large body of research in deep learning and machine learning * Participate in cutting-edge research for medical applications of computer vision Must Have Experience

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Medical Machine Learning information

See Georgia salary details

$30.8K

$139.1K

$284.6K

How much do medical machine learning jobs pay per year?

As of Sep 5, 2026, the average yearly pay for medical machine learning in Georgia is $139,096.00, according to ZipRecruiter salary data. Most workers in this role earn between $54,000.00 and $226,700.00 per year, depending on experience, location, and employer.

What is a medical machine learning?

A Medical Machine Learning job involves developing and applying AI algorithms to analyze medical data, such as imaging, electronic health records, and genomics, to improve diagnosis, treatment, and patient outcomes. Professionals in this field work with clinicians, data scientists, and engineers to create predictive models, automate medical workflows, and ensure compliance with healthcare regulations. Strong knowledge of machine learning, data processing, and healthcare-specific challenges is essential.

What types of teams do medical machine learning professionals typically collaborate with in a healthcare setting?

Medical Machine Learning professionals often work in multidisciplinary teams that include data scientists, clinicians, software engineers, and regulatory experts. Collaboration with healthcare providers is common to ensure models address real clinical needs and comply with healthcare standards. You'll typically interact closely with IT departments for data access and security, as well as with research teams and sometimes external partners. Working in such dynamic teams allows you to contribute technical expertise while gaining insights from domain experts, leading to more successful and impactful machine learning projects.

What are the key skills and qualifications needed to thrive in the medical machine learning position, and why are they important?

To thrive in Medical Machine Learning, you need a strong background in computer science, statistics, and biomedical sciences, often supported by an advanced degree in a related field. Familiarity with programming languages (such as Python or R), machine learning frameworks (like TensorFlow or PyTorch), and healthcare data management systems is crucial. Strong problem-solving abilities, collaboration skills, and the ability to communicate complex technical concepts to a diverse audience make a candidate stand out. These skills are critical for developing robust, effective machine learning solutions that can impact patient care and integrate seamlessly into clinical workflows.

What does medical machine learning do in healthcare?

Medical machine learning involves developing algorithms that analyze healthcare data to assist in diagnosis, treatment planning, and patient monitoring. Professionals in this field use tools like Python and TensorFlow to create models that improve accuracy and efficiency in medical decision-making.

What are the most commonly searched types of Medical Machine Learning jobs in Georgia?

The most popular types of Medical Machine Learning jobs in Georgia are:

What are popular job titles related to Medical Machine Learning jobs in Georgia?

For Medical Machine Learning jobs in Georgia, the most frequently searched job titles are:

What job categories do people searching Medical Machine Learning jobs in Georgia look for?

The top searched job categories for Medical Machine Learning jobs in Georgia are:

Medical Machine Learning jobs near you
Infographic showing various Medical Machine Learning job openings in Georgia as of August 2026, with employment types broken down into 1% As Needed, 70% Full Time, 15% Part Time, 11% Contract, and 3% Nights. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $139,096 per year, or $66.9 per hour.

Lead MLOps Engineer (Vertex AI & GCP)

Cognizant Technology Solutions

Atlanta, GA • On-site

$130K - $155K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 12 days ago

Key responsibilities

  • Lead the migration, containerization, and deployment of machine learning models into the Google Cloud Vertex AI ecosystem.

  • Design, implement, and maintain scalable CI/CD/CT pipelines using Vertex AI Pipelines, Kubeflow, Cloud Build, and related cloud-native technologies.

  • Develop and manage model deployment frameworks supporting real-time and batch inference workloads while ensuring reliability, scalability, and performance.

Cognizant rating

7.0

Company rating: 7.0 out of 10

Based on 87 frontline employees who took The Breakroom Quiz

59th of 72 rated business consultants

Job description

"Please note, this role is not able to offer visa transfer or sponsorship now or in the future."
About the role
As a Senior MLOps Engineer, you will make an impact by designing, implementing, and managing the cloud infrastructure, deployment pipelines, and monitoring frameworks that enable machine learning models to run reliably and efficiently in production environments. You will be a valued member of the AI & Data Engineering team and work collaboratively with Data Scientists, Data Engineers, business stakeholders, and global delivery teams to establish and scale MLOps capabilities on Google Cloud Platform (GCP).
In this role, you will:
  • Lead the migration, containerization, and deployment of existing machine learning models into the Google Cloud Vertex AI ecosystem.
  • Design, implement, and maintain scalable CI/CD/CT pipelines using Vertex AI Pipelines, Kubeflow, Cloud Build, and related cloud-native technologies.
  • Develop and manage model deployment frameworks supporting both real-time and batch inference workloads while ensuring reliability, scalability, and performance.
  • Establish monitoring, governance, and lifecycle management processes, including model drift detection, version control, model registry management, and rollback strategies.
  • Partner with business stakeholders, Data Science teams, and Data Engineering teams to define requirements, align priorities, and deliver enterprise-grade MLOps solutions.

Work model
We believe hybrid work is the way forward as we strive to provide flexibility wherever possible. Based on this role's business requirements, this is a hybrid position requiring regular onsite presence in Atlanta, Georgia. Regardless of your working arrangement, we are here to support a healthy work-life balance through our various wellbeing programs.
The working arrangements for this role are accurate as of the date of posting. This may change based on the project you're engaged in, as well as business and client requirements. Rest assured; we will always be clear about role expectations.
What you need to have to be considered
  • 7+ years of experience in Data Engineering, Software Engineering, Machine Learning Engineering, or a related technical field.
  • 3+ years of hands-on experience building and managing MLOps solutions and deploying machine learning models into production environments.
  • Strong expertise with Google Cloud Platform services, including Vertex AI, BigQuery, Cloud Storage, Pub/Sub, and related cloud-native technologies.
  • Advanced programming experience with Python and SQL, along with hands-on expertise in Docker, Kubernetes, and Google Kubernetes Engine (GKE).
  • Proven experience implementing CI/CD pipelines and Infrastructure as Code using tools such as Terraform, GitHub Actions, GitLab CI, Jenkins, or Cloud Build.
  • Demonstrated ability to lead technical initiatives, collaborate across distributed teams, and communicate effectively with both technical and non-technical stakeholders.

These will help you stand out
  • Google Cloud Professional Machine Learning Engineer or Professional Cloud Architect certification.
  • Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-Learn.
  • Experience implementing model monitoring, governance, and compliance frameworks in enterprise environments.
  • Familiarity with Agile and Scrum methodologies.
  • Experience mentoring engineers and leading offshore or distributed delivery teams.

We're excited to meet people who share our mission and can make an impact in a variety of ways. Don't hesitate to apply, even if you only meet the minimum requirements listed. Think about your transferable experiences and unique skills that make you stand out as someone who can bring new and exciting things to this role.
Applications will be accepted until September 29th, 2026.
Salary and Other Compensation:
The annual salary for this position is between $130,000 - $155,000 depending on experience and other qualifications of the successful candidate.
This position is also eligible for Cognizant's discretionary annual incentive program, based on performance and subject to the terms of Cognizant's applicable plans.
Benefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:
  • Medical/Dental/Vision/Life Insurance
  • Paid holidays plus Paid Time Off
  • 401(k) plan and contributions
  • Long-term/Short-term Disability
  • Paid Parental Leave
  • Employee Stock Purchase Plan

Disclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.
About Cognizant:
Cognizant (Nasdaq: CTSH) is an AI Builder and technology services provider, bridging the gap between AI investment and enterprise value by building full-stack AI solutions for our clients. Our deep industry, process and engineering expertise enables us to build an organization's unique context into technology systems that amplify human potential, drive tangible outcomes and keep global enterprises ahead in a fast-changing world. See how at cognizant.ai or @cognizant.
Additional employment information
Compensation information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.
Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government issued ID during each interview.
Cognizant is an equal opportunity employer. Your application and candidacy will not be considered based on race, color, sex, religion, creed, sexual orientation, gender identity, national origin, disability, genetic information, pregnancy, veteran status or any other characteristic protected by federal, state or local laws.
If you have a disability that requires reasonable accommodation to search for a job opening or submit an application, please email [email protected] for roles based in the Americas or [email protected] for roles based in India.

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