Machine Learning Engineer Salary in United States during 2023

Salary details

The average Machine Learning Engineer salary lies between USD 150,000 and USD 232,200 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 Machine Learning Engineer roles

The three most common job tag items assiciated with Machine Learning Engineer job listings are Machine Learning, Python and Engineering. 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:

Machine Learning | 1793 jobs Python | 1481 jobs Engineering | 1356 jobs Computer Science | 1038 jobs ML models | 1017 jobs PyTorch | 853 jobs TensorFlow | 782 jobs Research | 749 jobs Deep Learning | 730 jobs Pipelines | 703 jobs AWS | 651 jobs NLP | 610 jobs Statistics | 559 jobs Testing | 539 jobs Architecture | 529 jobs Mathematics | 462 jobs Java | 462 jobs SQL | 449 jobs Spark | 423 jobs GCP | 418 jobs

Top 20 Job Perks/Benefits for Machine Learning Engineer roles

The three most common job benefits and perks assiciated with Machine Learning 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 2023 and the number of open jobs that where offering them during that period:

Career development | 1495 jobs Health care | 752 jobs Flex hours | 644 jobs Equity / stock options | 631 jobs Startup environment | 531 jobs Flex vacation | 524 jobs Salary bonus | 479 jobs Competitive pay | 419 jobs Team events | 401 jobs Parental leave | 391 jobs Insurance | 339 jobs Medical leave | 322 jobs Wellness | 256 jobs 401(k) matching | 195 jobs Home office stipend | 176 jobs Conferences | 134 jobs Unlimited paid time off | 118 jobs Relocation support | 92 jobs Signing bonus | 84 jobs Flexible spending account | 83 jobs

Salary Composition for Machine Learning Engineers

The salary for a Machine Learning Engineer in the United States typically comprises a base salary, bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary is the fixed component and usually forms the largest part of the total compensation package. Bonuses can vary significantly depending on the company's performance, individual performance, and industry standards. In tech hubs like Silicon Valley, equity or stock options are common, providing employees with a stake in the company's success.

Regionally, salaries can vary, with higher compensation often found in tech-centric areas like San Francisco, Seattle, and New York City. Industry also plays a role; for instance, finance and tech companies might offer higher salaries compared to academia or smaller startups. Company size can influence the salary composition as well, with larger companies often providing more comprehensive benefits and bonuses.

Steps to Increase Salary

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

• Skill Enhancement: Continuously update your skills with the latest technologies and methodologies in AI/ML. Specializing in high-demand areas like deep learning, natural language processing, or computer vision can make you more valuable.

• Advanced Education: Pursuing further education, such as a master's or Ph.D., can open doors to higher-level positions and salary brackets.

• Networking and Industry Engagement: Attend conferences, workshops, and meetups to expand your professional network. Engaging with the community can lead to new opportunities and insights into higher-paying roles.

• Leadership Roles: Transitioning into leadership or managerial roles can significantly increase your earning potential. This might involve leading a team of engineers or managing projects.

• Negotiation Skills: Improve your negotiation skills to better advocate for higher pay during performance reviews or when switching jobs.

Educational Requirements

Most Machine Learning Engineer positions require at least a bachelor's degree in computer science, mathematics, statistics, or a related field. However, a master's degree or Ph.D. is often preferred, especially for roles involving complex research and development tasks. These advanced degrees provide a deeper understanding of machine learning algorithms, data analysis, and statistical modeling, which are crucial for the role.

Helpful Certifications

While not always mandatory, certain certifications can enhance your resume and demonstrate your expertise:

• Google Professional Machine Learning Engineer: Validates your ability to design, build, and productionize ML models on Google Cloud.

• AWS Certified Machine Learning – Specialty: Demonstrates your ability to build, train, tune, and deploy machine learning models on AWS.

• Microsoft Certified: Azure AI Engineer Associate: Shows proficiency in using Azure AI services to build and integrate AI solutions.

These certifications can be particularly beneficial if you're targeting roles that require specific cloud platform expertise.

Required Experience

Typically, employers look for candidates with 2-5 years of experience in machine learning or related fields. This experience should include hands-on work with machine learning frameworks (such as TensorFlow, PyTorch, or Scikit-learn), data preprocessing, model training, and deployment. Experience in software development and proficiency in programming languages like Python, R, or Java is also crucial.

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