Salary for Mid-level / Intermediate Machine Learning Engineer during 2023
💰 The median Salary for Mid-level / Intermediate Machine Learning Engineer during 2023 is USD 150,000
✏️ This salary info is based on 150 individual salaries reported during 2023
Salary details
The average mid-level / intermediate Machine Learning Engineer salary lies between USD 110,000 and USD 200,000 globally. 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.
- Job title
- Machine Learning Engineer
- Experience
- Mid-level / Intermediate
- Region
- global/worldwide
- Salary year
- 2023
- Sample size
- 150
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- Top 25%
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- Median
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All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.
Last updated: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 jobsTop 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 jobsSalary Composition
The salary for a mid-level Machine Learning Engineer 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 constitutes the majority of the total compensation package. Performance bonuses can vary significantly depending on the company's success and individual performance, often ranging from 10% to 20% of the base salary. Additional remuneration, like stock options, is more common in larger tech companies or startups, where they can form a significant part of the total compensation, sometimes matching or exceeding the base salary over time.
Regional differences also play a crucial role. For instance, salaries in tech hubs like San Francisco or New York are generally higher due to the cost of living and competition for talent. Industry-wise, sectors like finance, healthcare, and technology tend to offer higher salaries compared to academia or non-profit organizations. Company size can also influence salary composition, with larger companies often providing more comprehensive benefits and bonuses compared to smaller firms.
Increasing Salary
To increase your salary from a mid-level position, consider the following strategies:
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Skill Enhancement: Continuously update your skills in emerging areas of AI/ML, such as deep learning, natural language processing, or reinforcement learning. Mastering new tools and technologies can make you more valuable to employers.
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Advanced Education: Pursuing a master's or Ph.D. in a relevant field can open doors to higher-level positions and increase your earning potential.
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Networking: Building a strong professional network can lead to new opportunities and insights into higher-paying roles.
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Leadership Roles: Transitioning into roles that involve team leadership or project management can also lead to salary increases.
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Industry Switch: Moving to a higher-paying industry, such as finance or tech, can significantly boost your salary.
Educational Requirements
Most mid-level Machine Learning Engineer positions require at least a bachelor's degree in computer science, data science, mathematics, statistics, or a related field. However, a master's degree is often preferred and can be a significant advantage. Some roles may also require specific coursework or experience in machine learning, data analysis, and software development.
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 can validate your skills and knowledge, making you a more attractive candidate to potential employers.
Required Experience
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 with specific tools and frameworks like TensorFlow, PyTorch, or scikit-learn is often required. Additionally, experience in deploying machine learning models in production environments is highly valued.
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