Salary for Mid-level / Intermediate Machine Learning Engineer in United States during 2022

Salary details

The average mid-level / intermediate Machine Learning Engineer salary lies between USD 100,000 and USD 150,000 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. 24, 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 2022 and the number of open jobs that where associated with them during that period:

Machine Learning | 124 jobs Python | 108 jobs Engineering | 75 jobs AWS | 59 jobs Computer Science | 59 jobs ML models | 55 jobs TensorFlow | 52 jobs Research | 52 jobs PyTorch | 49 jobs Pipelines | 48 jobs NLP | 42 jobs Deep Learning | 36 jobs Testing | 36 jobs Spark | 31 jobs SQL | 30 jobs Docker | 28 jobs Big Data | 27 jobs Agile | 27 jobs Scikit-learn | 26 jobs PhD | 26 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 Team events. 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 | 110 jobs Health care | 57 jobs Team events | 34 jobs Flex hours | 33 jobs Equity / stock options | 31 jobs Competitive pay | 31 jobs Startup environment | 29 jobs Flex vacation | 25 jobs Conferences | 25 jobs Parental leave | 20 jobs Unlimited paid time off | 20 jobs Salary bonus | 14 jobs Fitness / gym | 10 jobs Insurance | 10 jobs Relocation support | 8 jobs Home office stipend | 7 jobs Gear | 5 jobs Medical leave | 5 jobs 401(k) matching | 4 jobs Wellness | 4 jobs

Salary Composition

The salary for a mid-level Machine Learning Engineer in the United States typically comprises a base salary, performance 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 bulk of the total compensation package. Performance bonuses can vary significantly depending on the company's profitability and individual performance metrics. Additional remuneration, like stock options, is more common in larger tech companies or startups, where equity is used as an incentive to attract and retain talent. Regional differences also play a role; for instance, salaries in tech hubs like San Francisco or New York City tend to be higher due to the cost of living and competitive job market. Industry-wise, sectors like finance, healthcare, and technology often offer higher compensation packages compared to academia or non-profit organizations.

Increasing Salary

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

• Skill Enhancement: Continuously update your skills with the latest technologies and tools 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 a master's or Ph.D. in a relevant field can open up higher-paying opportunities and leadership roles.
• Networking: Building a strong professional network can lead to new job opportunities and insights into higher-paying roles.
• Leadership Roles: Transitioning into roles with more responsibility, such as a team lead or project manager, can lead to salary increases.
• Industry Switch: Moving to a higher-paying industry or a larger company can also result in a significant salary bump.

Educational Requirements

Most mid-level Machine Learning Engineer positions require at least a bachelor's degree in computer science, mathematics, statistics, 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 research. A strong foundation in mathematics, particularly in linear algebra, calculus, and probability, is essential. Additionally, coursework or experience in programming languages like Python, R, or Java is often required.

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.
• AWS Certified Machine Learning – Specialty: Demonstrates your skills in building, training, and deploying ML models on the AWS platform.
• Microsoft Certified: Azure AI Engineer Associate: Focuses on using Azure services to build and deploy AI solutions.
• TensorFlow Developer Certificate: Shows proficiency in using TensorFlow for building and deploying ML models.

Required Experience

Typically, a mid-level Machine Learning Engineer is expected to have 3-5 years of experience in the field. This experience should include hands-on work with machine learning models, data analysis, and software development. Experience with data preprocessing, feature engineering, and model evaluation is crucial. Additionally, familiarity with ML frameworks like TensorFlow, PyTorch, or Scikit-learn is often required. Experience in deploying models to production and working in cross-functional teams is also highly valued.

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