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Senior Machine Learning Ops Engineer Jobs in Georgia

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global ... About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI ...

Senior Machine Learning Engineer

Atlanta, GA · On-site +1

$100K - $138K/yr

Position Overview As a Senior Machine Learning Engineer, you will play a key role in designing, developing, and evolving machine learning systems that support conversational AI, search, multi-agent ...

Senior Machine Learning Engineer

Atlanta, GA

$117K - $155K/yr

The Senior Full-Stack Machine Learning Engineer sits within the Insights Business Unit, which serves as Inovalon's central AI and machine learning hub. This team partners with Provider, Payer, and ...

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus ...

Senior Machine Learning Engineer

Atlanta, GA · On-site +1

$117K - $155K/yr

The Senior Full-Stack Machine Learning Engineer sits within the Insights Business Unit, which serves as Inovalon's central AI and machine learning hub. This team partners with Provider, Payer, and ...

Senior Machine Learning Test Engineer

Atlanta, GA · On-site +1

$106K - $138K/yr

Job Requisition ID # 26WD98377 Senior Machine Learning Test Engineer Location: United States East Coast Position Overview As a Senior Machine Learning Test Engineer in the Research Enablement team ...

Senior Machine Learning Engineer (Nova)

Atlanta, GA · On-site

$100K - $138K/yr

We are looking for a Senior Machine Learning Engineer to build the core Machine Learning ... email at talent-ops@iterable.com upon receiving a suspicious job offer. Criminal and/or civil ...

Senior Machine Learning Engineer

Atlanta, GA

$100K - $138K/yr

We are looking for Senior Machine Learning Engineer who may be looking to make the move to a big data environment. If this describes you, read on - we want to hear from you! THE GAME PLAN Everyone on ...

Senior Machine Learning Engineer

Atlanta, GA · On-site

$100K - $138K/yr

We are looking for Senior Machine Learning Engineer who may be looking to make the move to a big data environment. If this describes you, read on - we want to hear from you! THE GAME PLAN Everyone on ...

Senior Machine Learning Engineer

Atlanta, GA · On-site

$100K - $138K/yr

We are looking for Senior Machine Learning Engineer who may be looking to make the move to a big data environment. If this describes you, read on - we want to hear from you! THE GAME PLAN Everyone on ...

... Machine Learning driven features with Python (including NumPy, SciPy, Pandas, TensorFlow, Pytorch) Other Qualifications: * Strong programming skills in Python with proficiency in relevant libraries ...

GA

$100K - $138K/yr

Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next generation of voice and conversational AI agents within Realm-X. This role helps define AppFolio ...

Sr. Machine Learning Engineer

Atlanta, GA

$100K - $138K/yr

Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next generation of voice and conversational AI agents within Realm-X. This role helps define AppFolio ...

As a Senior ML Platform Engineer, you will contribute to building the ML platform at Prizepicks to scale and productionize our core machine learning capabilities. Your work will directly impact key ...

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Senior Machine Learning Ops Engineer information

What are the key skills and qualifications needed to thrive as a Senior Machine Learning Ops Engineer, and why are they important?

To thrive as a Senior Machine Learning Ops Engineer, you need expertise in machine learning, software engineering, cloud platforms, and experience with CI/CD pipelines, often supported by a computer science degree or equivalent experience. Proficiency with tools like Docker, Kubernetes, TensorFlow, PyTorch, and cloud services such as AWS, GCP, or Azure is typically required, along with familiarity with MLOps frameworks. Strong problem-solving, collaboration, and communication skills help you work effectively with cross-functional teams and manage complex ML model deployments. These skills are essential to ensure reliable, scalable, and efficient deployment of machine learning models in production environments.

What are some common challenges faced by Senior Machine Learning Ops Engineers when deploying models to production?

Senior Machine Learning Ops Engineers often encounter challenges such as ensuring model reproducibility, managing model versioning, and automating deployment pipelines for scalability. Another key challenge is monitoring model performance and data drift in production, which requires robust logging and alerting systems. Collaborating closely with data scientists, software engineers, and IT teams is essential to address these challenges and maintain a stable, efficient ML infrastructure.

What is the difference between Senior Machine Learning Ops Engineer vs Data Engineer?

AspectSenior Machine Learning Ops EngineerData Engineer
CredentialsExperience with ML frameworks, cloud platforms, scripting, and DevOps toolsStrong SQL, ETL, database, and programming skills, often with cloud experience
Work EnvironmentFocus on deploying, monitoring, and maintaining ML models in productionDesigning and building data pipelines and infrastructure for data processing
Industry UsageCommon in AI/ML-focused companies, tech firms, and data-driven organizationsWidespread across industries for data management and analytics

While both roles involve working with data and cloud platforms, the Senior Machine Learning Ops Engineer specializes in deploying and maintaining machine learning models, whereas the Data Engineer focuses on building data pipelines and infrastructure. Understanding these distinctions helps in choosing the right career path or job search focus.

What are Senior Machine Learning Ops Engineers?

Senior Machine Learning Ops (MLOps) Engineers are experienced professionals who design, build, and maintain the infrastructure and tools needed to deploy, monitor, and scale machine learning models in production environments. They work at the intersection of data science, software engineering, and DevOps to ensure ML models are robust, reliable, and secure. Their responsibilities often include automating model training pipelines, managing cloud resources, implementing CI/CD for ML, and ensuring model reproducibility. Senior MLOps Engineers also mentor junior staff and help define best practices for the organization’s ML workflow.
What are the most commonly searched types of Machine Learning Ops Engineer jobs in Georgia? The most popular types of Machine Learning Ops Engineer jobs in Georgia are:
What job categories do people searching Senior Machine Learning Ops Engineer jobs in Georgia look for? The top searched job categories for Senior Machine Learning Ops Engineer jobs in Georgia are:
What cities in Georgia are hiring for Senior Machine Learning Ops Engineer jobs? Cities in Georgia with the most Senior Machine Learning Ops Engineer job openings:
Infographic showing various Senior Machine Learning Ops Engineer job openings in Georgia as of June 2026, with employment types broken down into 55% Full Time, 26% Part Time, 4% Temporary, 13% Contract, and 2% Nights. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution.
Senior ML Ops Engineer

Senior ML Ops Engineer

RELX

Atlanta, GA

$112K - $179K/yr

Other

Posted 2 days ago


Job description

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 the team, this team that powers Elsevier's Health platforms: Clinical Key AI, Sherpath AI, and AI-driven automated clinical and content workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world's largest medical and scholarly landscapes.

About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality.

Key Responsibilities

ML & LLM Engineering, Search and Recommendation Engines

  • Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI).

  • Maintain and version model registries and artifact stores to ensure reproducibility and governance.

  • Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment.

  • Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML.

  • Scale end-end custom Sagemaker pipelines.

  • Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted.

  • Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs .

  • Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), and A/B testing.

  • Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization.

  • Stay current with the latest GAI research, NLP and RAG and apply the state-of-the-art in our experiments and systems.

Collaboration

  • Partner with Subject-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions

  • Collaborate and interface with Operations Engineers who deploy and run production infrastructure.

Qualifications

  • Current experience in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production.

  • Strong Python, Java, and/or Scala experience will be considered a plus.

  • Hands-on- experience with major cloud vendor solutions (AWS, Azure and/or Google)

  • Experience with Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr / Neo4j).

  • Experience in evaluating LLM models.

  • A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics.

  • Background in health technology and/or medical content workflows is preferred.

  • Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark.

  • Experience with large-scale data processing systems, e.g., Spark.

  • Experience with statistical analysis, machine learning theory and natural language processing.

Elsevier is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services. It is one of the largest publishers of academic journals and scholarly literature in the world. Elsevier operates in various domains, including science, technology, medicine, social sciences, and more. They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These journals act as platforms for researchers and academics to share their findings and contribute to the advancement of knowledge in their respective fields.

U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates.

If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New Jersey, the base pay range is $112,574 - $179,826.

This job is eligible for an annual incentive bonus.

We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here (https://www.relx.com/careers/join-us/benefits) to access benefits specific to your location.

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RELX is a global provider of information-based analytics and decision tools for professional and business customers, enabling them to make better decisions, get better results and be more productive.

Our purpose is to benefit society by developing products that help researchers advance scientific knowledge; doctors and nurses improve the lives of patients; lawyers promote the rule of law and achieve justice and fair results for their clients; businesses and governments prevent fraud; consumers access financial services and get fair prices on insurance; and customers learn about markets and complete transactions.

Our purpose guides our actions beyond the products that we develop. It defines us as a company. Every day across RELX our employees are inspired to undertake initiatives that make unique contributions to society and the communities in which we operate.