Machine Learning Engineer Salary in Netherlands during 2024
π° The median Machine Learning Engineer Salary in Netherlands during 2024 is USD 118,333
βοΈ This salary info is based on 8 individual salaries reported during 2024
Salary details
The average Machine Learning Engineer salary lies between USD 88,640 and USD 138,888 in the Netherlands. 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
- all levels
- Region
- Netherlands
- Salary year
- 2024
- Sample size
- 8
- Top 10%
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- Top 25%
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- Median
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- Bottom 25%
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- Bottom 10%
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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: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 | 6233 jobs Python | 4612 jobs Engineering | 4489 jobs Computer Science | 3611 jobs ML models | 3234 jobs PyTorch | 2965 jobs TensorFlow | 2731 jobs Research | 2475 jobs Pipelines | 2345 jobs Deep Learning | 2330 jobs NLP | 2096 jobs AWS | 2049 jobs LLMs | 1941 jobs Statistics | 1925 jobs Architecture | 1739 jobs Testing | 1523 jobs Spark | 1370 jobs SQL | 1353 jobs PhD | 1321 jobs Mathematics | 1305 jobsTop 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 | 5377 jobs Health care | 2889 jobs Equity / stock options | 2375 jobs Flex hours | 1704 jobs Flex vacation | 1619 jobs Startup environment | 1546 jobs Parental leave | 1411 jobs Competitive pay | 1395 jobs Salary bonus | 1372 jobs Medical leave | 1332 jobs Insurance | 1307 jobs Team events | 1083 jobs 401(k) matching | 898 jobs Conferences | 695 jobs Flexible spending account | 598 jobs Wellness | 582 jobs Home office stipend | 445 jobs Transparency | 302 jobs Relocation support | 289 jobs Unlimited paid time off | 187 jobsSalary Composition for Machine Learning Engineers in the Netherlands
The salary for a Machine Learning Engineer in the Netherlands typically comprises a fixed base salary, performance-based bonuses, and additional remuneration such as stock options or benefits. The fixed base salary is the most substantial component, often accounting for 70-80% of the total compensation package. Bonuses can vary significantly depending on the companyβs performance and individual achievements, usually ranging from 10-20% of the total salary. Additional remuneration might include stock options, especially in tech startups or large tech companies, and benefits such as health insurance, retirement plans, and transportation allowances. The composition can vary based on the region, with Amsterdam often offering higher salaries due to the cost of living, and industry, with tech and finance sectors typically providing more competitive packages. Larger companies might offer more comprehensive benefits, while startups might compensate with equity options.
Steps to Increase Salary from a Machine Learning Engineer Position
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 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: Engage with professional networks and communities. Attending conferences, meetups, and workshops can lead to new opportunities and insights into industry trends.
- Leadership Roles: Aim for roles with more responsibility, such as leading a team or managing projects, which often come with higher pay.
- Switching Companies: Sometimes, moving to a different company can result in a significant salary increase, especially if you have gained substantial experience and skills.
Educational Requirements for Machine Learning Engineers
Most 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. Advanced degrees provide a deeper understanding of complex algorithms and data structures, which are crucial in this field. Additionally, coursework in machine learning, artificial intelligence, and data analysis is highly beneficial.
Helpful Certifications for Machine Learning Engineers
While not always mandatory, certifications can enhance your resume and demonstrate your expertise. Some valuable certifications include:
- Google Professional Machine Learning Engineer: Validates your ability to design, build, and productionize ML models.
- AWS Certified Machine Learning β Specialty: Demonstrates your skills in building, training, tuning, and deploying ML models on AWS.
- 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 to build and train models.
Experience Requirements for Machine Learning Engineers
Typically, employers look for candidates with at least 2-5 years of experience in related fields. This experience should include hands-on work with machine learning models, data analysis, and programming. Experience with specific tools and frameworks like TensorFlow, PyTorch, or scikit-learn is often required. Additionally, experience in software development and a strong understanding of algorithms and data structures are crucial.
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