How to Become an MLOps Engineer

Your complete guide to breaking into this role, backed by data from 94+ job postings.

94
Jobs Available
$164K - $243K
Salary Range
28%
Remote
RAG
Top Skill Required

What Does a MLOps Engineer Do?

MLOps Engineers build and maintain the infrastructure that keeps ML models running in production. They handle CI/CD for models, monitoring, scaling, and the tooling that makes ML teams productive.

A Typical Day

  • Building ML training and serving infrastructure
  • Setting up model monitoring, logging, and alerting
  • Managing experiment tracking and model registries
  • Automating model retraining and deployment pipelines
  • Optimizing GPU utilization and inference costs

Required Skills

The most in-demand skills for MLOps Engineer roles, ranked by how often they appear in job postings.

  1. 1 RAG 72 jobs
  2. 2 Python 53 jobs
  3. 3 AWS 49 jobs
  4. 4 Azure 36 jobs
  5. 5 GCP 34 jobs
  6. 6 Rust 30 jobs
  7. 7 AI Agents 28 jobs
  8. 8 Kubernetes 28 jobs
  9. 9 Docker 23 jobs
  10. 10 PyTorch 16 jobs

Salary & Compensation

Based on 79 job postings with disclosed compensation ranges.

25th Percentile
$136K - $190K
Median
$159K - $239K
75th Percentile
$187K - $291K

Salary by Experience Level

LevelJobsSalary Range
Mid Level 5 $149K - $227K
Senior 74 $165K - $244K

Highest Paying Cities

MetroJobsAvg Salary Range
San Francisco 23 $193K - $280K
New York 6 $162K - $261K
Remote 4 $164K - $230K
Los Angeles 17 $151K - $229K
Boston 3 $114K - $172K

See full MLOps Engineer salary data →

How to Get Started

  1. 1

    Build Your Foundation

    Most MLOps Engineers come from DevOps, platform engineering, or backend software engineering. Strong infrastructure skills (Docker, Kubernetes, cloud platforms) are the foundation.

  2. 2

    Master the Core Skills

    Focus on the skills employers are asking for right now: RAG, Python, AWS. These are the top 3 skills appearing in MLOps Engineer job postings.

  3. 3

    Build Portfolio Projects

    Ship real projects that demonstrate your skills. Open-source contributions, personal projects, or freelance work all count. Hiring managers want to see what you can build, not just what you know.

  4. 4

    Apply Strategically

    Target companies actively hiring for this role. Top employers include Google, Amazon.com, BlueFlag LLP, Unknown. Tailor your resume to match the specific skills each company lists in their job descriptions.

Top Hiring Companies

Companies with the most MLOps Engineer job openings right now.

Career Progression

A typical career path for MLOps Engineer professionals.

MLOps Engineer
Senior MLOps Engineer
Staff MLOps Engineer
ML Platform Lead
VP of Engineering

Explore MLOps Engineer Careers

Related Roles

Frequently Asked Questions

Most people transition into MLOps Engineer roles within 6-18 months, depending on their starting background. Candidates with related experience (software engineering, data science, or adjacent fields) can move faster. There are currently 94 open MLOps Engineer positions in our database, so demand is strong for qualified candidates.
A formal degree helps but is not strictly required for most MLOps Engineer positions. Most MLOps Engineers come from DevOps, platform engineering, or backend software engineering. Strong infrastructure skills (Docker, Kubernetes, cloud platforms) are the foundation. Strong portfolio projects and relevant skills matter more than credentials at many companies.
Based on 79 job postings with disclosed compensation, MLOps Engineer salaries range from $164K - $243K. The highest-paying metro is San Francisco at $193K - $280K. 28% of these roles are fully remote.
The outlook is strong. We track 94 open MLOps Engineer positions across major job boards. 28% of current openings are remote, and the most requested skill is RAG. As AI adoption accelerates across industries, demand for MLOps Engineer professionals continues to grow.

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