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Ml Devops Engineer Jobs (NOW HIRING)

Azure DevOps Engineer

San Mateo, CA · On-site

$150K - $175K/yr

About the role We are seeking an Azure DevOps Engineer to be the foundational infrastructure hire ... Manage and support AI/ML workloads deployed on Azure, including Azure AI Foundry and related ...

Booz Allen is the leading provider of AI services to the nation, and we're looking for a DevOps engineer with knowledge of AIOps, ML Ops, model ops, and data ops to develop tools and get them into ...

DevOps Engineer

Arlington, VA · On-site

$77K - $176K/yr

Booz Allen is the leading provider of AI services to the nation, and we're looking for a DevOps engineer with knowledge of AIOps, ML Ops, model ops, and data ops to develop tools and get them into ...

DevOps Engineer

Arlington, VA · On-site

$77K - $176K/yr

Booz Allen is the leading provider of AI services to the nation, and we're looking for a DevOps engineer with knowledge of AIOps, ML Ops, model ops, and data ops to develop tools and get them into ...

Ai/ML Engineer

Dallas, TX · On-site

$85K - $107K/yr

Build and manage end-to-end ML/LLM pipelines on Azure ML using Azure DevOps for CI/CD, testing, and release automation. * Operationalize LLMs and generative AI solutions (e.g., GPT, LLaMA, Claude ...

DevOps Engineer

Arlington, VA · On-site

$77K - $176K/yr

Booz Allen is the leading provider of AI services to the nation, and we're looking for a DevOps engineer with knowledge of AIOps, ML Ops, model ops, and data ops to develop tools and get them into ...

DevOps Engineer

Chantilly, VA · On-site

$54 - $74/hr

DevOps Engineer Location: Chantilly VA We are looking for a DevOps Engineer with experience in building, delivering, and maintaining high-performing, scalable, enterprise-grade applications. You will ...

DevOps Engineer

Chantilly, VA · On-site

$54 - $74/hr

DevOps Engineer Location: Chantilly VA We are looking for a DevOps Engineer with experience in building, delivering, and maintaining high-performing, scalable, enterprise-grade applications. You will ...

DevOps Engineer

Bethesda, MD · On-site

$56.50 - $77.25/hr

We leverage cloud-based computing, artificial intelligence (Al), machine learning (ML) and cross ... As a Senior DevOps Engineer you will lead an DevOps team responsible for the design, deployment ...

DevOps Engineer

Hyattsville, MD · On-site

$131K - $237K/yr

We leverage cloud-based computing, artificial intelligence (Al), machine learning (ML) and cross ... As a Senior DevOps Engineer you will lead an DevOps team responsible for the design, deployment ...

DevOps Engineer

Arlington, VA · On-site

$131K - $237K/yr

We leverage cloud-based computing, artificial intelligence (Al), machine learning (ML) and cross ... As a Senior DevOps Engineer you will lead an DevOps team responsible for the design, deployment ...

DevOps Engineer

Bethesda, MD · On-site

$131K - $237K/yr

We leverage cloud-based computing, artificial intelligence (Al), machine learning (ML) and cross ... As a Senior DevOps Engineer you will lead an DevOps team responsible for the design, deployment ...

DevOps Engineer

Gaithersburg, MD · On-site

$131K - $237K/yr

We leverage cloud-based computing, artificial intelligence (Al), machine learning (ML) and cross ... As a Senior DevOps Engineer you will lead an DevOps team responsible for the design, deployment ...

DevOps Engineer

Rockville, MD · On-site

$131K - $237K/yr

We leverage cloud-based computing, artificial intelligence (Al), machine learning (ML) and cross ... As a Senior DevOps Engineer you will lead an DevOps team responsible for the design, deployment ...

DevOps Engineer

Washington, DC · On-site

$131K - $237K/yr

We leverage cloud-based computing, artificial intelligence (Al), machine learning (ML) and cross ... As a Senior DevOps Engineer you will lead an DevOps team responsible for the design, deployment ...

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Ml Devops Engineer information

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$19

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$90

How much do ml devops engineer jobs pay per hour?

As of Jun 29, 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.

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
Infographic showing various Ml Devops Engineer job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 78% Physical, 7% Hybrid, and 15% Remote job distribution, with an average salary of $122,950 per year, or $59.1 per hour.
DevOps Engineer II/ Senior

$136K - $175K/yr

Other

Posted 4 days ago


Rocket Lab rating

8.8

Company rating: 8.8 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

9th of 60 rated aerospace companies


Job description

SPACE SYSTEMS

At Rocket Lab, we're not just launching rockets - we're building the future of space. Our Space Systems team builds everything from complete spacecraft, precision payloads to the components and subsystems that allow them to thrive in space, like solar panels, flight software, star trackers, optical systems, separation systems, radios, and more. 

Our Space Systems team has enabled more than 1,700 missions, ranging from interplanetary exploration, in-space manufacturing to national security and defense initiatives. The team has built spacecraft, payloads, and components for missions to the Moon and Mars, working with partners including NASA, the Space Development Agency, and the U.S. Space Force. Whether it's a single high-performance spacecraft, constellation, or the vertically integrated components that help them get to space - our world class Space Systems team is empowering some of the boldest and most ambitious space missions. 

DEVOPS ENGINEER II/ SENIOR

As a DevOps Engineer II/ Senior based at Rocket Lab's global headquarters in Long Beach, CA, you will revolutionize software quality assurance through AI-driven automation and intelligent systems. This role sits within the DevSecOps organization and focuses on building autonomous AI ecosystems that continuously monitor, analyze, and improve software quality across all organizational programs and platforms. You will design and implement AI agents that automatically troubleshoot CI/CD testing failures, generate actionable insights, identify quality gaps, and proactively address findings within organizational software before they impact mission-critical operations. 

This is a highly technical, automation-focused role for someone who sees software quality engineering as an opportunity to build intelligent systems that work 24/7. You will create AI-powered reporting dashboards, automated notification systems, and predictive analytics that give leadership real-time visibility into software health across the entire organization. Your work will directly close quality gaps and elevate the security, reliability, and performance of software systems supporting space missions.

WHAT YOU'LL GET TO DO: 

  • Build and maintain AI-powered quality automation ecosystems that monitor CI/CD pipelines across multiple programs and platforms 
  • Design and implement AI agents that automatically detect, analyze, and troubleshoot software testing failures with minimal human intervention 
  • Develop intelligent reporting systems that provide real-time quality metrics, trend analysis, and actionable recommendations to leadership 
  • Create automated notification and alerting systems that proactively engage teams when quality issues are detected 
  • Identify and close quality gaps in organizational software through systematic analysis of findings, patterns, and root causes 
  • Leverage machine learning and AI tools to predict potential quality issues before they occur 
  • Integrate LLMs and AI assistants into testing workflows to enhance test coverage and defect detection 
  • Produce comprehensive automated test suites that run continuously in CI/CD pipelines 
  • Collaborate with DevSecOps teams to ensure security, quality, and compliance throughout the SDLC 
  • Drive continuous improvement through data-driven insights and AI-enhanced quality processes 
  • Manually test complex edge cases that AI systems flag as high-priority or difficult to automate 
  • Work with development teams through code reviews and integrated pipelines to ensure quality is built in from the start 

(Please note: This position can be hired at DevOps Engineer II or Senior DevOps Engineer I level.)

QUALIFICATIONS YOU'LL BRING AS DEVOPS ENGINEER II:

  • Bachelor's degree in Computer Science, Software Engineering, or other technical discipline 
  • 2+ years of experience in professional software development including software verification and validation practices 
  • Experience in AI/ML technologies with hands-on experience building AI-driven automation systems 
  • Demonstrated experience using AI tools, LLMs (ChatGPT, Claude, etc.), and AI coding assistants in daily workflows  
  • 2+ years of proficiency in Python skills with experience in AI/ML libraries and frameworks 
  • Knowledge of CI/CD pipeline automation tools and DevSecOps practices 
  • Experience with data analysis, metrics collection, and building reporting/dashboard systems 
  • Knowledge of the Software Development Life Cycle and V-Model 
  • U.S. citizenship is required, due to program requirements 

QUALIFICATIONS YOU'LL BRING AS SENIOR DEVOPS ENGINEER I:

  • Bachelor's degree in Computer Science, Software Engineering, or other technical discipline 
  • 5+ years of experience in professional software development including software verification and validation practices 
  • Experience in AI/ML technologies with hands-on experience building AI-driven automation systems 
  • Demonstrated experience using AI tools, LLMs (ChatGPT, Claude, etc.), and AI coding assistants in daily workflows  
  • 5+ years of proficiency in Python skills with experience in AI/ML libraries and frameworks 
  • Knowledge of CI/CD pipeline automation tools and DevSecOps practices 
  • Experience with data analysis, metrics collection, and building reporting/dashboard systems 
  • Knowledge of the Software Development Life Cycle and V-Model 
  • U.S. citizenship is required, due to program requirements 
THESE QUALIFICATIONS WOULD BE NICE TO HAVE:
  • Active Secret or Top Secret Clearance
  • Experience with AI agent frameworks, autonomous systems, or multi-agent orchestration
  • Proven track record building intelligent automation solutions that solve complex software quality engineering problems
  • Background in machine learning, natural language processing, or predictive analytics
  • Proficiency in C and C++ languages
  • Strong problem-solving skills with an automation-first mindset
  • Proven track record producing or testing high-quality software in CI/CD pipelines
  • Experience building dashboards using tools like Grafana, Kibana, or custom visualization frameworks
  • Knowledge of security testing tools and DevSecOps security practices
  • Aerospace background supporting satellite, spacecraft, constellation, or launch vehicle ground/mission operations
  • Demonstrated leadership in testing design and working with engineering teams
  • Ability to produce clear, well-structured, and well-documented designs
  • Expertise in Git-based workflows, CI/CD pipelines, and Kubernetes orchestration
  • Experience with observability and monitoring tools (Prometheus, ELK stack, etc.)
This position may require prolonged periods of sitting, standing, walking, computer work, and occasional exposure to moderate levels of noise, dust, and fumes in production areas.