MLOps Engineer Salary in 2024

Salary details

The average MLOps Engineer salary lies between USD 117,800 and USD 198,000 globally. It represents the overall compensation/gross salary amount for the working year (before deductions like social security, taxes and other contributions), not including equity/stock options or similar benefits.

All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.

Last updated: Feb. 16, 2025

Salary trend

Top 20 Job Tags for MLOps Engineer roles

The three most common job tag items assiciated with MLOps Engineer job listings are MLOps, Machine Learning and Python. Below you find a list of the 20 most occuring job tags in 2024 and the number of open jobs that where associated with them during that period:

MLOps | 357 jobs Machine Learning | 350 jobs Python | 303 jobs Pipelines | 290 jobs Engineering | 287 jobs Kubernetes | 252 jobs ML models | 248 jobs CI/CD | 236 jobs Docker | 222 jobs AWS | 217 jobs DevOps | 207 jobs Azure | 175 jobs PyTorch | 164 jobs Computer Science | 161 jobs TensorFlow | 156 jobs Testing | 154 jobs GCP | 151 jobs MLFlow | 135 jobs Security | 128 jobs Architecture | 127 jobs

Top 20 Job Perks/Benefits for MLOps Engineer roles

The three most common job benefits and perks assiciated with MLOps Engineer job listings are Career development, Health care and Flex hours. Below you find a list of the 20 most occuring job perks or benefits in 2024 and the number of open jobs that where offering them during that period:

Career development | 264 jobs Health care | 114 jobs Flex hours | 99 jobs Competitive pay | 83 jobs Startup environment | 75 jobs Team events | 72 jobs Equity / stock options | 67 jobs Flex vacation | 66 jobs Parental leave | 41 jobs Insurance | 38 jobs Salary bonus | 33 jobs Medical leave | 32 jobs Transparency | 25 jobs 401(k) matching | 24 jobs Wellness | 24 jobs Gear | 18 jobs Home office stipend | 18 jobs Conferences | 14 jobs Unlimited paid time off | 14 jobs Relocation support | 13 jobs

Salary Composition for MLOps Engineers

The salary composition for an MLOps Engineer can vary significantly based on factors such as region, industry, and company size. Typically, the salary is divided into three main components: base salary, bonuses, and additional remuneration such as stock options or benefits.

• Base Salary: This is the fixed annual amount and usually constitutes the largest portion of the total compensation. In tech hubs like Silicon Valley, New York, or Seattle, the base salary might be higher due to the cost of living and competitive job market.

• Bonuses: These are performance-based and can vary widely. In larger tech companies or financial institutions, bonuses can be substantial, sometimes up to 20-30% of the base salary, depending on individual and company performance.

• Additional Remuneration: This includes stock options, profit-sharing, and other benefits like health insurance, retirement plans, and paid time off. Startups might offer more in stock options as a way to attract talent, while established companies might provide more comprehensive benefits packages.

Steps to Increase Salary from MLOps Engineer Position

To increase your salary from an MLOps Engineer position, consider the following strategies:

• Skill Enhancement: Continuously update your skills in the latest AI/ML tools and technologies. Specializing in niche areas like deep learning, natural language processing, or cloud-based MLOps can make you more valuable.

• Advanced Education: Pursuing a master's degree or Ph.D. in a related field can open up higher-paying opportunities and leadership roles.

• Networking: Engage with professional communities, attend conferences, and participate in workshops to expand your network and learn about new opportunities.

• Leadership Roles: Aim for roles that involve team leadership or project management, as these often come with higher pay.

• Switching Companies: Sometimes, moving to a different company can result in a significant salary increase, especially if you are moving to a larger or more prestigious organization.

Educational Requirements for MLOps Engineers

Most MLOps Engineer positions require at least a bachelor's degree in computer science, engineering, mathematics, or a related field. However, many employers prefer candidates with a master's degree or higher, especially for senior roles. Coursework in machine learning, data science, software engineering, and cloud computing is particularly beneficial.

Helpful Certifications for MLOps Engineers

Certifications can enhance your resume and demonstrate your expertise to potential employers. Some valuable certifications include:

• AWS Certified Machine Learning – Specialty
• Google Professional Machine Learning Engineer
• Microsoft Certified: Azure AI Engineer Associate
• Certified Kubernetes Administrator (CKA)
• TensorFlow Developer Certificate

These certifications validate your skills in specific tools and platforms commonly used in MLOps.

Experience Required for MLOps Engineers

Typically, employers look for candidates with 3-5 years of experience in related fields such as software engineering, data engineering, or DevOps. Experience with machine learning frameworks, cloud platforms, and CI/CD pipelines is often required. For senior roles, 5-10 years of experience with demonstrated leadership in projects or teams may be necessary.

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