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Senior Machine Learning Ops Engineer Jobs in Georgia

Iterable

Senior Machine Learning Engineer (Nova)

Atlanta, GA · On-site

$100K - $138K/yr

They are seeking a Senior Machine Learning Engineer to build core Machine Learning foundations, focusing on applied Machine Learning in production environments, and collaborating with various teams ...

Warnerbros

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 Warner Bros. Discovery (WBD) is home to the world's most iconic entertainment, news, and sports ...

New

Inovalon

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

Senior Machine Learning Engineer

Atlanta, GA · Remote

$165K - $225K/yr

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 ...

Inovalon, Inc.

Senior Machine Learning Engineer

Atlanta, GA · On-site

$118K - $155K/yr

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

Inovalon

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 ...

Autodesk

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 ...

Iterable

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 ...

FanDuel

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 ...

FanDuel

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 ...

FanDuel

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 ...

Ksb

Machine Learning Engineer

Grovetown, GA

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

Workday, Inc.

Senior/Principal AI Engineer

Atlanta, GA · On-site

$120K - $166K/yr

About the Role As a Senior/Principal Machine Learning Engineer in Agent Factory, you'll design and build the core ML systems behind Workday's next generation of AI agents. Working within a small ...

Workday

Senior/Principal AI Engineer

Atlanta, GA

$120K - $166K/yr

About the Role As a Senior/Principal Machine Learning Engineer in Agent Factory, you'll design and build the core ML systems behind Workday's next generation of AI agents. Working within a small ...

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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:
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Senior Machine Learning Ops Engineer jobs near you
Senior Machine Learning Engineer (Nova)

Senior Machine Learning Engineer (Nova)

Iterable

Atlanta, GA • On-site

$100K - $138K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Job Summary:
Iterable is the leading AI-powered customer engagement platform that helps brands create dynamic, individualized experiences at scale. They are seeking a Senior Machine Learning Engineer to build core Machine Learning foundations, focusing on applied Machine Learning in production environments, and collaborating with various teams to enhance the Iterable platform.
Responsibilities:
• Design and build Machine Learning platform components that support agentic systems, including retrieval pipelines, indexing strategies, and model integration layers.
• Introduce and operationalize RAG use cases, from data sourcing and embedding generation to runtime retrieval patterns.
• Develop generalized evaluation frameworks for LLM- and agent-based features, including offline metrics, golden datasets, and continuous monitoring.
• Implement abstractions, tooling, and reusable patterns that enable other teams to build ML- and LLM-powered experiences efficiently.
• Partner with backend engineers to productionize ML features with strong reliability, observability, and performance characteristics.
• Prototype applied ML solutions to validate feasibility before investing in full builds.
• Ensure secure, robust handling of data used in ML workflows and retrieval operations.
• Collaborate with product, design, and engineering to align ML system design with user experience and product goals.
• Contribute to iterative improvements of the Nova agent framework, including workflows built with Mastra and TypeScript.
Qualifications:
Required:
• 5+ years experience as a Machine Learning Engineer or similar role focused on production systems.
• Strong engineering skills with Python or TypeScript, including experience building ML workflows in frameworks like Mastra or comparable agent/LLM toolkits.
• Experience with retrieval systems, vector databases, search technologies, or RAG architectures.
• Prior work integrating ML or LLM-powered features into production applications.
• Understanding of ML evaluation techniques, experimentation design, and failure analysis.
• Ability to lead complex projects, make practical trade-offs, and work independently in areas of ambiguity.
• Strong communication and collaboration skills in a distributed environment.
Preferred:
• Experience building ML or LLM platforms, tooling, or developer-facing frameworks.
• Prior work with embeddings, search–ranking systems, or advanced RAG architectures.
• Familiarity with event-driven systems or streaming architectures.
• Experience with model observability, performance monitoring, or proactive regression detection.
• Background in personalization, recommendations, or applied NLP.
• Experience working in remote-first engineering teams.
Company:
Iterable is an AI-powered communication platform that improves customer retention with its marketing. Founded in 2013, the company is headquartered in San Francisco, USA, with a team of 501-1000 employees. The company is currently Late Stage.

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