MLOps Engineer Salary in United States during 2024

Salary details

The average MLOps Engineer salary lies between USD 125,000 and USD 210,000 in the United States. 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.

Region represents the primary country of residence of an employee during the year (or residence for tax purposes). All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.

Last updated: Nov. 17, 2024

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 | 308 jobs Machine Learning | 302 jobs Python | 264 jobs Engineering | 251 jobs Pipelines | 247 jobs ML models | 222 jobs Kubernetes | 217 jobs CI/CD | 200 jobs Docker | 188 jobs AWS | 183 jobs DevOps | 173 jobs PyTorch | 144 jobs Azure | 144 jobs Computer Science | 141 jobs Testing | 140 jobs TensorFlow | 138 jobs GCP | 129 jobs Architecture | 115 jobs MLFlow | 114 jobs Model training | 110 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 | 231 jobs Health care | 100 jobs Flex hours | 89 jobs Competitive pay | 74 jobs Startup environment | 72 jobs Equity / stock options | 66 jobs Team events | 59 jobs Flex vacation | 53 jobs Parental leave | 39 jobs Insurance | 35 jobs Medical leave | 30 jobs Salary bonus | 30 jobs Wellness | 24 jobs Transparency | 19 jobs Gear | 18 jobs 401(k) matching | 16 jobs Home office stipend | 16 jobs Conferences | 14 jobs Relocation support | 13 jobs Unlimited paid time off | 13 jobs

Salary Composition for MLOps Engineers

The salary for an MLOps Engineer in the United States typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary is the fixed component and usually constitutes the majority of the total compensation package. Performance bonuses can vary significantly depending on the company's success and individual performance, often ranging from 10% to 20% of the base salary. Additional remuneration, such as stock options, is more common in larger tech companies or startups and can significantly increase the total compensation, especially if the company performs well. Regional differences also play a role; for instance, salaries in tech hubs like San Francisco or New York City tend to be higher due to the cost of living and competitive job market. Industry-wise, tech companies, financial services, and healthcare often offer higher salaries compared to other sectors.

Steps to Increase Salary

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

• Skill Enhancement: Continuously update your skills with the latest tools and technologies in AI/ML and MLOps. Specializing in niche areas like AI ethics, data privacy, or advanced machine learning algorithms 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.
• Leadership Roles: Transitioning into managerial or leadership roles within the MLOps domain can lead to significant salary increases.
• Networking: Building a strong professional network can lead to opportunities in higher-paying companies or industries.
• Negotiation: Always negotiate your salary and benefits when offered a new position or during performance reviews.

Educational Requirements

Most MLOps Engineer positions require at least a bachelor's degree in computer science, data science, engineering, or a related field. However, a master's degree is often preferred and can be a significant advantage. Courses in machine learning, data engineering, cloud computing, and software development are particularly relevant. Some positions may also require knowledge of specific programming languages like Python, R, or Java, and familiarity with cloud platforms such as AWS, Azure, or Google Cloud.

Helpful Certifications

Certifications can enhance your resume and demonstrate your expertise to potential employers. Some valuable certifications for MLOps Engineers 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 deploying and managing machine learning models and working with cloud platforms, which are crucial for MLOps roles.

Required Experience

Typically, MLOps Engineer roles require 3-5 years of experience in related fields such as software engineering, data engineering, or machine learning. Experience with DevOps practices, CI/CD pipelines, and containerization technologies like Docker and Kubernetes is often essential. Hands-on experience with machine learning frameworks and cloud services is also highly valued.

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