Machine Learning Engineer Salary in United States during 2024

Salary details

The average Machine Learning Engineer salary lies between USD 147,400 and USD 250,000 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: Dec. 22, 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 2024 and the number of open jobs that where associated with them during that period:

Machine Learning | 6280 jobs Python | 4647 jobs Engineering | 4521 jobs Computer Science | 3632 jobs ML models | 3264 jobs PyTorch | 2988 jobs TensorFlow | 2751 jobs Research | 2489 jobs Pipelines | 2365 jobs Deep Learning | 2341 jobs NLP | 2112 jobs AWS | 2063 jobs LLMs | 1955 jobs Statistics | 1940 jobs Architecture | 1750 jobs Testing | 1543 jobs Spark | 1382 jobs SQL | 1366 jobs PhD | 1326 jobs Mathematics | 1318 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 Equity / stock options. 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 | 5411 jobs Health care | 2912 jobs Equity / stock options | 2392 jobs Flex hours | 1717 jobs Flex vacation | 1635 jobs Startup environment | 1559 jobs Parental leave | 1424 jobs Competitive pay | 1404 jobs Salary bonus | 1377 jobs Medical leave | 1342 jobs Insurance | 1315 jobs Team events | 1089 jobs 401(k) matching | 906 jobs Conferences | 699 jobs Flexible spending account | 599 jobs Wellness | 588 jobs Home office stipend | 447 jobs Transparency | 302 jobs Relocation support | 291 jobs Unlimited paid time off | 188 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 such as San Francisco, Seattle, and New York City. Industry also plays a role; for instance, finance and tech companies tend to offer higher salaries compared to academia or smaller startups. Company size can influence the compensation structure, 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:

• 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.
• Pursue Leadership Roles: Transitioning into roles such as a lead engineer or manager can significantly increase your earning potential.
• Continuous Learning and Upskilling: Stay updated with the latest technologies and methodologies in AI/ML. Advanced courses or certifications can enhance your skill set and make you more valuable.
• Network and Build a Personal Brand: Attend industry conferences, contribute to open-source projects, and publish research to build your reputation in the field.
• Negotiate Offers: When changing jobs, negotiate your salary and benefits package effectively. Use industry salary data to support your case.

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. Advanced degrees provide a deeper understanding of algorithms, data structures, and statistical models, which are crucial for developing sophisticated machine learning solutions.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credentials and demonstrate your expertise to potential employers. 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 validate your skills in specific platforms and tools, making you more competitive in the job market.

Required Experience

Typically, employers look for candidates with at least 2-5 years of experience in machine learning or related fields. Experience with data analysis, software development, and working with machine learning frameworks like TensorFlow, PyTorch, or scikit-learn is often required. Practical experience in deploying machine learning models in production environments is highly valued.

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