Salary for Mid-level / Intermediate Machine Learning Engineer in United States during 2023

Salary details

The average mid-level / intermediate Machine Learning Engineer salary lies between USD 126,277 and USD 200,000 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 Mid-level / Intermediate Machine Learning Engineer roles

The three most common job tag items assiciated with mid-level / intermediate 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 | 235 jobs Python | 191 jobs Engineering | 166 jobs ML models | 133 jobs Computer Science | 133 jobs Research | 116 jobs PyTorch | 111 jobs TensorFlow | 102 jobs NLP | 98 jobs Deep Learning | 93 jobs Pipelines | 93 jobs AWS | 91 jobs Statistics | 84 jobs Scikit-learn | 71 jobs Architecture | 71 jobs Testing | 59 jobs Docker | 59 jobs GCP | 57 jobs SQL | 56 jobs Computer Vision | 53 jobs

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

The three most common job benefits and perks assiciated with mid-level / intermediate 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 | 208 jobs Health care | 107 jobs Flex hours | 80 jobs Startup environment | 80 jobs Flex vacation | 73 jobs Equity / stock options | 65 jobs Competitive pay | 56 jobs Team events | 50 jobs Parental leave | 44 jobs Salary bonus | 36 jobs Insurance | 34 jobs Medical leave | 28 jobs Unlimited paid time off | 28 jobs Conferences | 22 jobs Wellness | 21 jobs Home office stipend | 19 jobs 401(k) matching | 18 jobs Relocation support | 18 jobs Fitness / gym | 16 jobs Gear | 10 jobs

Salary Composition

The salary for a mid-level Machine Learning Engineer in the United States typically comprises a base salary, bonuses, and additional remuneration such as stock options or benefits. 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, bonuses and stock options can be substantial, often making up a significant portion of the total compensation. In contrast, companies in regions with a lower cost of living might offer smaller bonuses but a competitive base salary. Larger companies or those in high-demand industries like finance or tech often provide more comprehensive compensation packages, including benefits like health insurance, retirement plans, and professional development opportunities.

Increasing Salary

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

• Skill Enhancement: Continuously update your skills in emerging technologies and tools in AI/ML. Specializing in niche areas like deep learning, natural language processing, or computer vision can make you more valuable.
• Advanced Education: Pursuing a master's or Ph.D. in a relevant field can open doors to higher-level positions and salaries.
• Networking: Engage with professional networks and communities. Attending conferences, meetups, and workshops can lead to new opportunities and insights into industry trends.
• Leadership Roles: Transitioning into roles that involve team leadership or project management can increase your earning potential.
• Industry Shift: Moving to industries with higher pay scales, such as finance or healthcare, can also result in a salary increase.

Educational Requirements

Most mid-level Machine Learning Engineer positions require at least a bachelor's degree in computer science, data science, mathematics, or a related field. However, many employers prefer candidates with a master's degree or higher, especially for roles that involve complex problem-solving and advanced algorithm development. A strong foundation in statistics, linear algebra, and programming is essential, and coursework in machine learning, data mining, and artificial intelligence is highly beneficial.

Helpful Certifications

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

• 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 attractive to potential employers.

Experience Requirements

Typically, a mid-level Machine Learning Engineer is expected to have 3-5 years of relevant experience. This experience should include hands-on work with machine learning models, data analysis, and software development. Experience in deploying machine learning models in production environments and working with large datasets is often required. Familiarity with programming languages such as Python, R, or Java, and experience with machine learning frameworks like TensorFlow, PyTorch, or scikit-learn are also common requirements.

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