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Mlops Machine Learning Engineer Jobs in Georgia (NOW HIRING)

Staff Machine Learning Engineer

Atlanta, GA · On-site +1

$220K - $280K/yr

As a Staff Machine Learning Engineer, you will lead the technical charge to scale and productionize ... End-to-End MLOps Leadership: Champion best practices for model deployment, monitoring, and CI/CD ...

Staff Machine Learning Engineer

Atlanta, GA · On-site +1

$220K - $280K/yr

As a Staff Machine Learning Engineer, you will lead the technical charge to scale and productionize ... End-to-End MLOps Leadership: Champion best practices for model deployment, monitoring, and CI/CD ...

Machine Learning Engineer - South Bank, QLD Apply now Refer a friend Job no: 530695 Brand: Product ... Build endtoend MLOps pipelines including CI/CD, model registries, monitoring, drift detection and ...

Machine Learning Engineer KSB GIW, Inc. Department: Engineering, Research & Development Reports to: Metallurgical and Materials R&D Lab Manager Location: Grovetown, GA, USA (onsite) Shift: First FLSA ...

New

Machine Learning Engineer

Atlanta, GA · On-site

$85.92 - $130/hr

* Senior MLOps Engineer (Contractor) About the Role: * Client is seeking an experienced Senior MLOps Engineer to join client's Data Science Enablement (MLOps) team as a contractor. * Candidates will be ...

Senior Machine Learning Engineer

Atlanta, GA · On-site

$100K - $138K/yr

Senior Machine Learning Engineer Team: Data & Audience Platform (DAP) - ML Engineering What We Do ... MLOps & Infrastructure Champion MLOps best practices: model versioning, champion/challenger ...

New

CNN is a global leader in news and information, seeking a Machine Learning Engineer I to build and deploy ML systems that enhance personalization, search, recommendations, and content understanding ...

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a ... Understanding of FDA regulatory requirements for AI/ML in medical devices Experience with MLOps ...

Staff Machine Learning Engineer

Atlanta, GA · On-site +1

$162K - $342K/yr

As a Staff Machine Learning Engineer , you will design, build, and deploy machine learning systems that power predictive analytics, personalization, automation, and intelligent platform behaviors.You ...

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Showing results 1-20

Mlops Machine Learning Engineer information

What does an MLOps Machine Learning Engineer do?

An MLOps Machine Learning Engineer bridges the gap between data science and IT operations by developing, deploying, and maintaining machine learning models in production environments. They are responsible for automating workflows, managing model versioning, monitoring performance, and ensuring scalability and reliability of ML systems. Their work enables organizations to deploy machine learning solutions efficiently and consistently, making it easier to update and manage models as business needs evolve.

How does an MLOps Machine Learning Engineer typically collaborate with data scientists and software engineers during the deployment of machine learning models?

An MLOps Machine Learning Engineer acts as a bridge between data scientists and software engineers, ensuring machine learning models transition smoothly from development to production. They often work closely with data scientists to understand model requirements, data pipelines, and performance metrics, while also collaborating with software engineers to integrate models into scalable systems. Regular communication, shared documentation, and joint troubleshooting sessions are common, as the role requires aligning model performance with system reliability and maintainability. This collaborative environment helps ensure that models are robust, scalable, and impactful in real-world applications.

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

AspectMlops Machine Learning EngineerData Scientist
Required CredentialsBachelor's or master's in CS, data science, or related fields; certifications in cloud platforms or MLOps toolsBachelor's or master's in statistics, data science, or related fields; certifications in data analysis or machine learning
Work EnvironmentFocus on deploying, maintaining, and scaling ML models in production environmentsFocus on data analysis, model development, and insights generation
Employer & Industry UsageTech companies, startups, enterprises implementing ML solutionsResearch institutions, analytics firms, tech companies for data insights

While both roles involve machine learning, Mlops Machine Learning Engineers specialize in deploying and maintaining models in production, ensuring scalability and reliability. Data Scientists primarily focus on developing models and analyzing data to generate insights. The roles often overlap but differ in their core responsibilities and work environments.

What are the key skills and qualifications needed to thrive as an MLOps Machine Learning Engineer, and why are they important?

To thrive as an MLOps Machine Learning Engineer, you need a strong background in machine learning concepts, software engineering, and cloud infrastructure, typically supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (AWS, GCP, Azure), and certifications such as Google Professional Machine Learning Engineer are highly beneficial. Strong problem-solving abilities, collaboration, and communication skills help you work effectively across data science and engineering teams. These skills are essential for reliably deploying, monitoring, and maintaining scalable machine learning solutions in production environments.
What cities in Georgia are hiring for Mlops Machine Learning Engineer jobs? Cities in Georgia with the most Mlops Machine Learning Engineer job openings:
Machine Learning Engineer

Machine Learning Engineer

Intuitive

Peachtree Corners, GA • On-site

Full-time

Re-posted 24 days ago


Job description

Company Description

It started with a simple idea: what if surgery could be less invasive and recovery less painful? Nearly 30 years later, that question still fuels everything we do at Intuitive. As a global leader in robotic-assisted surgery and minimally invasive care, our technologies-like the da Vinci surgical system and Ion-have transformed how care is delivered for millions of patients worldwide.

We're a team of engineers, clinicians, and innovators united by one purpose: to make surgery smarter, safer, and more human. Every day, our work helps care teams perform with greater precision and patients recover faster, improving outcomes around the world.

The problems we solve demand creativity, rigor, and collaboration. The work is challenging, but deeply meaningful-because every improvement we make has the potential to change a life.

If you're ready to contribute to something bigger than yourself and help transform the future of healthcare, you'll find your purpose here.

Job Description

Role

We are looking for a talented individual to join our growing machine learning and data science team to help provide creative ways to develop new technology focused on surgical workflow and performance for next generation robotic surgery platforms.

As a Machine Learning Engineer, you will work at the intersection of machine learning and engineering (i.e., MLOps) to contribute to innovative digital solutions leveraging Surgical AI/ML technologies. Immediate projects and responsibilities may include:

  • Integrating machine learning into digital products and services by working cross-functionally across engineering, data science, and machine learning teams

  • Developing automated workflows and tools to curate datasets and facilitate training of deep learning models

  • Working closely with Machine Learning and Data/Software Engineering teams to develop efficient processes for model development/deployment for various applications.

  • Help support and manage a growing cloud infrastructure for MLOps

Qualifications

What you'll need to be successful:

  • M.S. or Ph.D. in computer science, electrical and computer engineering, or related fields.

  • Minimum 3 years of industry experience developing productionized code in machine learning, data engineering, or related field for AI applications

  • Excellent communication skills both written and verbal

  • A desire to work in a high-energy, focused, small-team environment with a sense of shared responsibility and shared reward

  • Interest in early research and development through to product roll-out in the fields of surgical AI and surgical robotics

  • Hands-on experience with ML frameworks, such as PyTorch, Tensorflow, or similar

  • Knowledgeable about MLOps platforms (Domino Data Labs) and/or ML CI/CD workflows to manage datasets and model training, deployment, and monitoring

  • Experience with MLOps tools like MLFlow, KubeFlow, W&B, etc

  • Knowledgeable about Kubernetes

  • Experience with cloud compute environments such as AWS, GCP, etc

  • Experience with both edge and cloud deployments, focused on automation, scalability, and robustness

  • Experience with Python and SQL

  • Experience with Git e.g github, gitlab, bitbucket, etc

  • Ability to travel domestically and internationally (5-10%)

Additional desirable experience:

  • Experience with successfully launching ML models into production

  • Experience supporting large multi-modality dataset including image/video

  • Experience within healthcare

  • Experience with federated learning

Additional Information

Due to the nature of our business and the role, please note that Intuitive and/or your customer(s) may require that you show current proof of vaccination against certain diseases including COVID-19.  Details can vary by role.

Intuitive is an Equal Opportunity Employer. We provide equal employment opportunities to all qualified applicants and employees, and prohibit discrimination and harassment of any type, without regard to race, sex, pregnancy, sexual orientation, gender identity, national origin, color, age, religion, protected veteran or disability status, genetic information or any other status protected under federal, state, or local applicable laws.

Mandatory Notices

U.S. Export Controls Disclaimer:  In accordance with the U.S. Export Administration Regulations (15 CFR 743.13(b)), some roles at Intuitive Surgical may be subject to U.S. export controls for prospective employeeswho are nationals from countries currently on embargo or sanctions status.

Certain information you provide as part of the application will be used for purposes of determining whether Intuitive Surgical will need to (i) obtain an export license from the U.S. Government on your behalf (note: the government's licensing process can take 3 to 6+ months) or (ii) implement a Technology Control Plan ("TCP") (note: typically adds 2 weeks to the hiring process).  

For any Intuitive role subject to export controls, final offers are contingent upon obtaining an approved export license and/or an executed TCP prior to the prospective employee'sstart date, which may or may not be flexible, and within a timeframe that does not unreasonably impede the hiring need. If applicable, candidates will be notified and instructed on any requirements for these purposes. 

We will consider for employment qualified applicants with arrest and conviction records in accordance with fair chance laws.

Preference will be given to qualified candidates who do not reside, or plan to reside, in Alabama, Arkansas, Delaware, Florida, Indiana, Iowa, Louisiana, Maryland, Mississippi, Missouri, Oklahoma, Pennsylvania, South Carolina, or Tennessee.

This position may be filled at a different job level than listed here depending on
business need and/or on the selected candidate's experience, knowledge and skills.
Compensation will be based primarily on the job level at which the role is filled and the
candidate's qualifications, consistent with applicable law.

We provide market-competitive compensation packages, inclusive of base pay, incentives, benefits, and equity. It would not be typical for someone to be hired at the top end of range for the role, as actual pay will be determined based on several factors, including experience, skills, and qualifications. The target compensation ranges are listed.