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Ml Devops Engineer Jobs (NOW HIRING)

Fantom Corporation

DevOps Engineer

Chantilly, VA

$54 - $74/hr

We are seeking a DevOps Engineer to design, implement, and maintain secure DevOps infrastructure ... Learning (ML) with a focus on identifying trends, object detection, and classification of ...

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 ...

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 ...

CUBRC Inc.

DevOps Engineer

Buffalo, NY · On-site

$93K - $142K/yr

As a DevOps engineer, you will be helping configure and maintain processes that automate software ... ML and AI enabled software tools supporting our defense, intelligence and homeland security ...

Atkore

AI DevOps Engineer

Mokena, IL · On-site

$52 - $71/hr

AI DevOps Engineer You must be authorized to work in the U.S. without any current or future ... Azure ML Studio, Mflow, etc) * Strong understanding of enterprise security principles, identity ...

Atkore International Group

AI DevOps Engineer

Mokena, IL

$52 - $71/hr

AI DevOps Engineer You must be authorized to work in the U.S. without any current or future ... Azure ML Studio, Mflow, etc) * Strong understanding of enterprise security principles, identity ...

Atkore International Group

AI DevOps Engineer

Dallas, TX

$48.25 - $66/hr

AI DevOps Engineer You must be authorized to work in the U.S. without any current or future ... Azure ML Studio, Mflow, etc) * Strong understanding of enterprise security principles, identity ...

PROLIM Global Corporation

Sr. Devops Engineer

Austin, TX · On-site

$128K - $165K/yr

Prolim is hiring for a Devops Engineer for a leading client. Contract: Long term Location: Austin ... AI/ML concepts and platform integration 8 Required Experience with Azure Monitoring and Log ...

Atkore Management, LLC

AI DevOps Engineer

Mokena, IL

$52 - $71/hr

AI DevOps Engineer You must be authorized to work in the U.S. without any current or future ... Azure ML Studio, Mflow, etc) * Strong understanding of enterprise security principles, identity ...

Atkore Management, LLC

AI DevOps Engineer

Dallas, TX

$48.25 - $66/hr

AI DevOps Engineer You must be authorized to work in the U.S. without any current or future ... Azure ML Studio, Mflow, etc) * Strong understanding of enterprise security principles, identity ...

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 ...

FICO

Lead ML Ops/DevOps Engineer - AI Engineering

$140K - $220K/yr

Partner with DevOps and SRE teams to ensure high availability, observability, scalability, and security of the data and ML infrastructure. * Work closely with Data Scientists and ML Engineers to ...

Zensors

ML Ops / Dev Ops Engineer

San Francisco, CA · On-site

$62.25 - $85/hr

About the Role As an ML / DevOps Engineer, you will play a pivotal role in advancing our infrastructure, scaling enterprise deployment workflows, and refining automation architectures to enable rapid ...

TEKsystems

Devops Engineer

Mitchell, SD

$70K - $130K/yr

Exposure to AI/ML tools or platforms, including AI Foundry or agent-based frameworks * Background in telecommunications or SaaS environments * Experience working in DevOps transformation initiatives ...

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Ml Devops Engineer information

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How much do ml devops engineer jobs pay per hour?

As of Jul 20, 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.

Is DevOps dead due to AI?

DevOps engineers focus on automating and streamlining software development and deployment processes. While AI tools are increasingly used to enhance automation and monitoring, they complement rather than replace the core DevOps practices, making the role still relevant and evolving with new technologies.

What engineer makes $500,000 a year?

A senior or lead Machine Learning DevOps Engineer with extensive experience, advanced skills in cloud platforms, automation, and infrastructure management can earn $500,000 or more annually, especially in high-cost-of-living areas or large tech companies. Such roles often require strong expertise in tools like Kubernetes, Docker, and CI/CD pipelines, along with relevant certifications and a track record of managing complex ML deployment environments.

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.

Is DevOps still in demand in 2026?

DevOps engineers remain in high demand in 2026 due to the ongoing need for automation, continuous integration, and deployment in software development. Skills in cloud platforms, containerization, and automation tools like Jenkins and Kubernetes are especially valuable in this field.

What is the salary of DevOps engineer vs ML engineer?

DevOps engineers typically earn between $80,000 and $140,000 annually, depending on experience and location, while ML engineers often have salaries ranging from $100,000 to $160,000 or higher. ML engineers usually require specialized skills in machine learning frameworks and data handling, which can influence compensation levels.

What are ML DevOps Engineers?

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? The top searched job categories for Ml Devops Engineer jobs are:
Ml Devops Engineer jobs near you
Infographic showing various Ml Devops Engineer job openings in the United States as of July 2026, with employment types broken down into 92% Full Time, 1% Part Time, and 7% Contract. Highlights an 77% Physical, 6% Hybrid, and 17% Remote job distribution, with an average salary of $122,950 per year, or $59.1 per hour.
DevOps Engineer

DevOps Engineer

Fantom Corporation

Chantilly, VA

$54 - $74/hr

Full-time

Posted 19 days ago

Job description

Fantom Corporation is a mission-focused organization supporting critical programs across the defense and intelligence community. We partner with our customers to deliver high-impact technical solutions while fostering a culture built on trust, expertise, and long-term career growth.

We are seeking a DevOps Engineer to design, implement, and maintain secure DevOps infrastructure and development environments. This role is responsible for leveraging modern DevOps tools, containerization technologies, and cloud services to support software development, production operations, and pilot programs across secure on-premises and AWS cloud environments.

The ideal candidate has experience building scalable CI/CD pipelines, managing containerized applications, automating infrastructure, and supporting mission-critical systems in secure enterprise environments.

Responsibilities
  • Design, implement, and maintain secure DevOps environments supporting software development and production operations
  • Build and manage CI/CD pipelines to automate application deployment, testing, and release processes
  • Deploy, configure, and maintain containerized applications and orchestration platforms
  • Support development teams by providing reliable build, integration, and deployment environments
  • Manage infrastructure across on-premises systems and AWS cloud environments
  • Automate infrastructure provisioning, configuration management, and deployment workflows
  • Monitor system health, application performance, and infrastructure availability while implementing improvements to reliability and scalability
  • Troubleshoot and resolve infrastructure, deployment, and application issues across development and production environments
  • Collaborate with software developers, systems engineers, and security teams to integrate DevSecOps best practices throughout the software development lifecycle
  • Support pilot programs by rapidly deploying and maintaining new development environments and technical capabilities
  • Develop and maintain technical documentation, automation scripts, and operational procedures
  • Ensure platform security, compliance, and operational readiness across enterprise environments
Required Qualifications
  • Must be fully cleared with a recent polygraph
  • Must be willing and able to work fully onsite at the location listed in this posting
  • Experience as a DevOps Engineer, Cloud Engineer, Systems Engineer, or similar technical role
  • Experience designing and supporting CI/CD pipelines and automated deployment processes
  • Experience with containerization technologies such as Docker and Kubernetes
  • Experience supporting AWS cloud services and hybrid cloud environments
  • Experience administering Linux-based systems
  • Experience with infrastructure automation and configuration management tools
  • Strong scripting and automation skills using Bash, Python, or similar languages
  • Experience with version control systems such as Git
  • Strong troubleshooting and problem-solving skills in complex technical environments
  • Excellent written and verbal communication skills
  • Ability to work collaboratively within Agile and cross-functional engineering teams
Desired Qualification
  • Experience supporting secure or classified environments
  • Experience implementing DevSecOps best practices
  • Experience with Infrastructure as Code (Terraform, CloudFormation, or similar)
  • Experience with monitoring and logging platforms
  • AWS cloud certifications or Kubernetes certifications
  • Experience supporting enterprise production systems and pilot technology initiatives
  • #CJ
Fantom Corp is a Software Development, Agile Cloud, Software Development, Cyber Security (Risk Management, Assessments & Authorization (A&A)), Data, AI Platform (Computer Vision Models), Podcasting Media Services, and IT Services provider. Established in 2015, Fantom Corp serves Federal customers with top-notch Cybersecurity Architects, Data Scientists/Analysts, Software Engineers/Developers, DevSecOps Engineers, Project Managers, Identity, Credential Access Management (ICAM) services , and Cloud-certified practitioners. We excel in delivering emerging technologies such as Artificial Intelligence (AI) and Machine Learning (ML) with a focus on identifying trends, object detection, and classification of structured and unstructured data. Fantom Corp possesses mastery in all aspects of digital audio production. We lead in the ideation and creation of efforts for clients who want to harness the power of podcasting. We guide them in selecting the right show format for their needs and goals. As a Small Business, we possess the innovation, speed and flexibility to meet your requirements. 

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.