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Ml Devops Engineer Jobs (NOW HIRING)

Synergy ECP

Senior DevOps Engineer

Columbia, MD · On-site

$126K - $162K/yr

They are seeking a highly experienced and technically proficient Senior DevOps Engineer to focus on ... ML engineers and data scientists to streamline deployment processes and optimize resource ...

Gormat

Senior DevOps Engineer

Annapolis Junction, MD · On-site

$132K - $170K/yr

Collaborate with AI/ML engineers and data scientists to streamline deployment processes and ... Advanced proficiency in DevOps principles and practices. * Demonstrated expertise in ...

Learn Beyond Consulting LLC

AI Devops Engineer

Atlanta, GA · On-site

$50.75 - $69.50/hr

AI/ML Operations & Observability: Hands-on experience supporting production AI/ML environments with ... DevOps Engineer IV to support the design, implementation, and optimization of enterprise AI ...

Gormat

Senior DevOps Engineer

Annapolis Junction, MD · On-site

$132K - $170K/yr

Collaborate with AI/ML engineers and data scientists to streamline deployment processes and ... Advanced proficiency in DevOps principles and practices. * Demonstrated expertise in ...

Gormat

Senior DevOps Engineer

Annapolis Junction, MD · On-site

$195K - $210K/yr

Collaborate with AI/ML engineers and data scientists to streamline deployment processes and ... Continuously research and implement new DevOps tools and practices to enhance efficiency.Required ...

Synergy ECP

Senior DevOps Engineer

Columbia, MD · On-site

$126K - $162K/yr

They are seeking a highly experienced Senior DevOps Engineer to focus on deploying infrastructure ... ML engineers and data scientists to streamline deployment processes and optimize resource ...

ACI Infotech

senior DevOps Engineer

Vienna, VA · On-site

$130K - $167K/yr

Senior DevOps Engineer Duration: 12+ Months Location: VA Senior DevOps Engineer that would ... ML, federated queries, ML, security - Expose data sources - Incorporate federation - expose data ...

Inspire11

DevOps Engineer

Chicago, IL · On-site

$54.50 - $74.50/hr

... ML and agentic AI technologies to DevOps workflows and platform engineering; staying current with AI-assisted pipeline tooling, intelligent observability, LLM-powered automation patterns ...

4pconsultinginc

DevOps Engineer 4

Atlanta, GA · On-site

$50.75 - $69.50/hr

... DevOps Engineer (Level 4) to join our team. This role focuses on designing, deploying, and ... Build and maintain CI/CD pipelines to support ML models, data workflows, and web applications.

Elliptic

Senior DevOps Engineer

New York, NY · Remote

$140K - $260K/yr

Elliptic is looking for a Senior DevOps Engineer to join our DevOps team. This is a hands-on ... You don't need to be an ML engineer, but you should be comfortable deploying, securing, and ...

Lorvenk Technologies LLC

Azure Devops Engineer

Mashpee, MA · On-site

$54.25 - $74.25/hr

Azure Devops Engineer Client: UniFirst Location: Wilmington, MA Locals Experience : 11+ Hybrid: 3 ... Knowledge of AI/ML workflows, model deployment, or MLOps concepts (preferred but not required)

New

Venus Consultancy

DevOps Engineer

Cambridge, MA · On-site

$57.75 - $79/hr

DevOps Engineer U.S. GenAI startup, Cambridge Office Full-Time Employment with We . We are ... Knowledge of AI/ML infrastructure requirements and optimization * Experience with GPU orchestration ...

Copart, Inc.

Senior DevOps Engineer

Dallas, TX · On-site

$128K - $165K/yr

Position Overview We are seeking a highly skilled Mid-Level to Senior DevOps Engineer with hands-on ... Deploy, manage, and optimize AI/ML workloads in production environments. * Support LLM-based ...

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Showing results 21-40

All JobsMl Devops Engineer Jobs

ML Devops Engineer information

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$90

How much do ml devops engineer jobs pay per hour?

As of Aug 13, 2026, the average hourly pay for ml devops engineer in the United States is $59.11, according to ZipRecruiter salary data. Most workers in this role earn between $48.32 and $69.23 per hour, depending on experience, location, and employer.

How does an ML DevOps engineer typically collaborate with data scientists and software engineers on machine learning projects?

An ML DevOps Engineer plays a crucial role in bridging the gap between data scientists and software engineers by operationalizing machine learning models. They work closely with data scientists to understand model requirements and assist in preparing models for deployment, ensuring scalability and reliability. Additionally, they collaborate with software engineers to integrate models into production systems, automate workflows, and maintain infrastructure. This cross-functional teamwork often involves regular meetings, code reviews, and shared documentation, fostering a collaborative and agile environment.

What is the difference between Ml Devops Engineer vs Data Scientist?

AspectMl Devops EngineerData Scientist
Required SkillsMachine learning, DevOps tools, scripting, cloud platformsStatistics, data analysis, machine learning, programming
Work EnvironmentCollaborates with DevOps and ML teams, focuses on deployment and automationAnalyzes data, builds models, interprets results
CertificationsCloud certifications, ML certifications, DevOps toolsData science certifications, statistical courses

The main difference between an Ml Devops Engineer and a Data Scientist lies in their focus areas. Ml Devops Engineers specialize in deploying, automating, and maintaining machine learning models within production environments, combining DevOps practices with ML expertise. Data Scientists primarily focus on analyzing data, building models, and deriving insights. Both roles require knowledge of machine learning, but their responsibilities and skill sets differ significantly.

What are the key skills and qualifications needed to thrive as an ML DevOps engineer, and why are they important?

To thrive as an ML DevOps Engineer, you need strong skills in machine learning, software engineering, and cloud infrastructure, often supported by a degree in computer science or related fields. Familiarity with tools like Docker, Kubernetes, CI/CD systems, and platforms such as AWS or Azure, as well as experience with MLOps frameworks, is typically required. Excellent problem-solving, collaboration, and communication skills help you bridge the gap between data science and engineering teams. These competencies are crucial for reliably deploying, scaling, and maintaining machine learning models in production environments.

Are ML Devops engineers still in demand?

ML DevOps engineers are in high demand due to the increasing adoption of machine learning models in production environments. Skills in cloud platforms, containerization, automation, and monitoring are highly valued as organizations seek to deploy scalable and reliable AI solutions.

What is an ML DevOps engineer?

ML DevOps Engineers are professionals who bridge the gap between machine learning (ML) development and operations (DevOps). They are responsible for automating, deploying, monitoring, and maintaining machine learning models in production environments. Their work ensures that ML models are scalable, reliable, and integrated seamlessly within an organization's infrastructure. ML DevOps Engineers collaborate with data scientists, software engineers, and IT teams to streamline the ML lifecycle from model development to deployment and monitoring.
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What job categories do people searching Ml Devops Engineer jobs look for?

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ML Devops Engineer jobs near you
Infographic showing various Ml Devops Engineer job openings in the United States as of August 2026, with employment types broken down into 92% Full Time, 2% Part Time, and 6% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $122,950 per year, or $59.1 per hour.

Senior DevOps Engineer

Synergy ECP

Columbia, MD • On-site

$126K - $162K/yr

Full-time

Re-posted 2 days ago

Job description

Job Summary:
Synergy ECP is a leading provider of cybersecurity, software and systems engineering and IT services to the U.S. intelligence and defense communities. They are seeking a highly experienced and technically proficient Senior DevOps Engineer to focus on deploying infrastructure and engineering workflows for enterprise AI rollouts.
Responsibilities:
• Design, implement, and maintain robust infrastructure for enterprise AI applications in cloud environments (AWS, Microsoft Azure)
• Develop and optimize engineering workflows and processes to support AI model development, deployment, and maintenance.
• Architect and manage CI/CD pipelines for continuous integration and continuous delivery of AI models and applications.
• Implement and manage containerization solutions using technologies like Docker and Kubernetes.
• Ensure efficient AI model lifecycle management, including versioning, monitoring, and scaling.
• Collaborate with AI/ML engineers and data scientists to streamline deployment processes and optimize resource utilization.
• Oversee system performance, security, and scalability of AI infrastructure.
• Continuously research and implement new DevOps tools and practices to enhance efficiency.
Qualifications:
Required:
• B.S. in a relevant technical field with 12 years of experience, or M.S. in a relevant technical field with 10 years of experience.
• Advanced proficiency in DevOps principles and practices.
• Demonstrated expertise in containerization using Docker and Kubernetes.
• Proven experience in architecting and managing CI/CD pipelines.
• Extensive experience with AI model lifecycle management and maintenance.
• Familiarity with cloud platforms (AWS, Microsoft Azure) for infrastructure deployment and management.
• Familiarity with monitoring and logging tools (e.g., Prometheus, Grafana, ELK stack).
• Excellent communication and interpersonal skills, with the ability to effectively collaborate with cross-functional teams.
• Ability to translate complex technical concepts into actionable engineering solutions.
• TS/SCI with CI Poly.
• U.S. Citizenship
Preferred:
• Experience with infrastructure as code (IaC) tools (e.g., Terraform, Ansible).
• Understanding of machine learning concepts and their implications for infrastructure.
• Continuous learning mindset to stay abreast of cutting-edge DevOps and AI advancements.
Company:
Synergy ECP deals with cybersecurity, information technology, procurement support, project management and financial analysis. Founded in 2007, the company is headquartered in Columbia, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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