Salary for Mid-level / Intermediate MLOps Engineer during 2023

Salary details

The average mid-level / intermediate MLOps Engineer salary lies between USD 73,100 and USD 134,000 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: Dec. 22, 2024

Salary trend

Top 20 Job Tags for Mid-level / Intermediate MLOps Engineer roles

The three most common job tag items assiciated with mid-level / intermediate MLOps Engineer job listings are MLOps, Machine Learning and CI/CD. Below you find a list of the 20 most occuring job tags in 2023 and the number of open jobs that where associated with them during that period:

MLOps | 20 jobs Machine Learning | 19 jobs CI/CD | 16 jobs Python | 15 jobs Pipelines | 15 jobs Engineering | 13 jobs DevOps | 13 jobs AWS | 12 jobs ML models | 12 jobs TensorFlow | 11 jobs PyTorch | 11 jobs Kubernetes | 10 jobs Testing | 10 jobs Computer Science | 10 jobs SQL | 8 jobs Research | 8 jobs Security | 8 jobs Azure | 8 jobs Docker | 8 jobs Airflow | 7 jobs

Top 20 Job Perks/Benefits for Mid-level / Intermediate MLOps Engineer roles

The three most common job benefits and perks assiciated with mid-level / intermediate MLOps Engineer job listings are Career development, Health care and Startup environment. Below you find a list of the 20 most occuring job perks or benefits in 2023 and the number of open jobs that where offering them during that period:

Career development | 17 jobs Health care | 7 jobs Startup environment | 6 jobs Team events | 6 jobs Competitive pay | 4 jobs Parental leave | 3 jobs Flex hours | 3 jobs Flex vacation | 3 jobs Snacks / Drinks | 3 jobs Gear | 2 jobs Relocation support | 2 jobs Salary bonus | 2 jobs Unlimited paid time off | 2 jobs Equity / stock options | 1 jobs Transparency | 1 jobs Conferences | 1 jobs Medical leave | 1 jobs Insurance | 1 jobs

Salary Composition for a Mid-level MLOps Engineer

The salary for a Mid-level MLOps Engineer typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or benefits. 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 might include stock options, especially in tech companies or startups, and benefits like health insurance, retirement plans, and paid time off.

Regional differences can also impact salary composition. For instance, tech hubs like Silicon Valley or New York City might offer higher base salaries and more lucrative stock options compared to other regions. Industry and company size also play a role; larger companies or those in high-demand sectors like finance or healthcare may offer more competitive compensation packages.

Steps to Increase Salary from a Mid-level Position

To increase your salary from a mid-level MLOps Engineer position, consider the following strategies:

• Skill Enhancement: Continuously update your technical skills, especially in emerging technologies and tools relevant to MLOps, such as Kubernetes, Docker, and cloud platforms like AWS, Azure, or Google Cloud.
• Advanced Certifications: Obtain advanced certifications in AI/ML or cloud computing, which can make you more valuable to employers.
• Networking: Build a strong professional network by attending industry conferences, joining relevant online communities, and engaging with thought leaders in the field.
• Leadership Roles: Seek opportunities to lead projects or teams, which can demonstrate your capability for higher-level positions.
• Negotiation: When discussing salary, be prepared to negotiate based on your contributions, market research, and the value you bring to the company.

Educational Requirements

Most mid-level MLOps Engineer positions require at least a bachelor's degree in computer science, engineering, data science, or a related field. However, a master's degree can be advantageous and is often preferred by employers, especially for roles that involve complex problem-solving and advanced technical skills. A strong foundation in mathematics, statistics, and programming is essential.

Helpful Certifications

Certifications can enhance your credentials and demonstrate your expertise in specific areas. Some valuable certifications for MLOps Engineers include:

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

These certifications validate your skills in managing machine learning operations and cloud-based solutions, making you a more attractive candidate to potential employers.

Required Experience

Typically, a mid-level MLOps Engineer is expected to have 3-5 years of experience in related roles, such as software engineering, data engineering, or DevOps. Experience with machine learning frameworks, cloud platforms, and automation tools is crucial. Employers also look for a proven track record of deploying and managing machine learning models in production environments.

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