Salary for Senior-level / Expert Machine Learning Engineer in United States during 2022

Salary details

The average senior-level / expert Machine Learning Engineer salary lies between USD 142,200 and USD 204,500 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. 24, 2024

Salary trend

Top 20 Job Tags for Senior-level / Expert Machine Learning Engineer roles

The three most common job tag items assiciated with senior-level / expert Machine Learning Engineer job listings are Machine Learning, Python and Engineering. Below you find a list of the 20 most occuring job tags in 2022 and the number of open jobs that where associated with them during that period:

Machine Learning | 731 jobs Python | 594 jobs Engineering | 588 jobs ML models | 430 jobs Computer Science | 370 jobs TensorFlow | 339 jobs Research | 320 jobs Pipelines | 312 jobs PyTorch | 310 jobs Deep Learning | 281 jobs AWS | 273 jobs Spark | 233 jobs Testing | 220 jobs NLP | 209 jobs SQL | 192 jobs Statistics | 173 jobs Scikit-learn | 172 jobs Kubernetes | 166 jobs GCP | 163 jobs Agile | 163 jobs

Top 20 Job Perks/Benefits for Senior-level / Expert Machine Learning Engineer roles

The three most common job benefits and perks assiciated with senior-level / expert Machine Learning Engineer job listings are Career development, Health care and Flex vacation. Below you find a list of the 20 most occuring job perks or benefits in 2022 and the number of open jobs that where offering them during that period:

Career development | 591 jobs Health care | 249 jobs Flex vacation | 230 jobs Flex hours | 220 jobs Startup environment | 180 jobs Team events | 176 jobs Equity / stock options | 164 jobs Parental leave | 153 jobs Competitive pay | 133 jobs Insurance | 124 jobs Medical leave | 123 jobs Salary bonus | 85 jobs Conferences | 74 jobs Home office stipend | 68 jobs Wellness | 65 jobs Unlimited paid time off | 59 jobs 401(k) matching | 58 jobs Flexible spending account | 50 jobs Snacks / Drinks | 23 jobs Gear | 22 jobs

Salary Composition

The salary for a Senior-level or Expert Machine Learning Engineer in the United States typically comprises several components: a fixed base salary, performance-based bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary is the largest component and can vary significantly depending on the region, industry, and company size. For instance, tech hubs like Silicon Valley or New York City often offer higher base salaries compared to other regions due to the higher cost of living and competitive job market. Bonuses are usually tied to individual performance, team success, or company profitability and can range from 10% to 20% of the base salary. Additional remuneration, such as stock options, is more common in startups or large tech companies and can significantly increase total compensation, especially if the company performs well.

Increasing Salary

To increase your salary further from a Senior-level Machine Learning Engineer position, consider the following strategies:

• Specialize in High-Demand Areas: Focus on niche areas within AI/ML, such as deep learning, natural language processing, or computer vision, which are in high demand and can command higher salaries.
• Leadership Roles: Transition into leadership or managerial roles, such as a Machine Learning Team Lead or Director of AI, which typically offer higher compensation.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML. Pursuing advanced certifications or courses can make you more valuable to employers.
• Networking: Build a strong professional network to learn about high-paying opportunities and negotiate better offers.
• Consulting or Freelancing: Consider consulting or freelancing, which can offer higher hourly rates and the flexibility to work on multiple projects.

Educational Requirements

Most Senior-level Machine Learning Engineer positions require at least a master's degree in a relevant field such as Computer Science, Data Science, Statistics, or Electrical Engineering. A Ph.D. is often preferred, especially for roles that involve research or developing new algorithms. The educational background should include a strong foundation in mathematics, statistics, and computer programming.

Helpful Certifications

While not always required, certain certifications can enhance your credentials and demonstrate expertise in specific areas. Some valuable certifications include:

• Google Professional Machine Learning Engineer
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate
• TensorFlow Developer Certificate

These certifications can validate your skills in using specific platforms and tools, making you more attractive to potential employers.

Required Experience

Typically, a Senior-level Machine Learning Engineer is expected to have at least 5-10 years of experience in the field. This experience should include hands-on work with machine learning models, data analysis, and software development. Experience in leading projects or teams, as well as a proven track record of deploying machine learning solutions in production environments, is highly valued.

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