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Ml Devops Engineer Jobs (NOW HIRING)

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 ...

Apex Systems

DevOps Engineer

Bentonville, AR · On-site

$45 - $61.50/hr

Experience supporting ML/AI workloads, including model serving infrastructure and GPU provisioning. * Google Cloud Platform Professional DevOps Engineer or Cloud Architect certification.

Fantom Corporation

DevOps Engineer

Chantilly, VA · On-site

$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 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 ...

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

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 Management, LLC

AI DevOps Engineer

Dallas, TX · On-site

$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

Dallas, TX · On-site

$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 ...

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 ...

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ML Devops Engineer information

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$19

$59

$90

How much do ml devops engineer jobs pay per hour?

As of Jul 23, 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.
More about ML Devops Engineer jobs
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 90% Full Time, 2% Part Time, and 8% Contract. Highlights an 75% Physical, 8% Hybrid, and 17% Remote job distribution, with an average salary of $122,950 per year, or $59.1 per hour.

AI DevOps Engineer

Rootshell Enterprise Technologies, Inc.

Santa Clara, CA • On-site

$61.50 - $84.25/hr

Full-time

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

Job description

Hello All,
Greetings from Rootshell Inc.
Rootshell Enterprise Technologies Inc. is a recognized provider of professional IT Consulting services in the US. We are actively seeking AI DevOps Engineer for one of our client, Please share your resume with current location & full contact info
Role: AI DevOps Engineer
Location:Santa Clara, CA(Onsite)
Job description:
• Familiar with the fundamentals of artificial intelligence and machine learning.
• Ideally have (but not required) Hands-on experience with open-source AI models
• Proven fast learning capability.
Technical Skills:
• Proficiency in scripting and automation languages or AI tools (Python, Bash, Jupiter Notebook, Golang, etc.).
• Familiarity with one of following: AI models (hugging face, Claude, etc.), ML frameworks (TensorFlow, PyTorch, etc.), deployment tools (e.g., MLflow, Seldon, or TFX)
• Solid understanding of computer algorithms, AI training, inference, and AI powered use cases
• Good to have infrastructure as code (IaC) tools like Terraform or Ansible.
With regards
Naveen | Talent Acquisition
Rootshell Enterprise Technologies Inc.
Naveen@rootshellinc.com | www.rootshellinc.com

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