Salary for Senior-level / Expert Machine Learning Engineer in Germany during 2024

💰 The median Salary for Senior-level / Expert Machine Learning Engineer in Germany during 2024 is USD 173,888

✏️ This salary info is based on 10 individual salaries reported during 2024

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Salary details

The average senior-level / expert Machine Learning Engineer salary lies between USD 137,777 and USD 212,000 in Germany. 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
Senior-level / Expert
Region
Germany
Salary year
2024
Sample size
10
Top 10%
$ 216,000
Top 25%
$ 212,000
Median
$ 173,888
Bottom 25%
$ 137,777
Bottom 10%
$ 93,300

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 Senior-level / Expert Machine Learning Engineer roles

The three most common job tag items assiciated with senior-level / expert 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 | 3308 jobs Python | 2582 jobs Engineering | 2454 jobs Computer Science | 2012 jobs ML models | 1820 jobs PyTorch | 1752 jobs TensorFlow | 1617 jobs Deep Learning | 1408 jobs Pipelines | 1355 jobs Research | 1328 jobs AWS | 1234 jobs LLMs | 1155 jobs NLP | 1145 jobs Architecture | 1076 jobs Statistics | 1038 jobs Testing | 934 jobs Spark | 838 jobs GCP | 767 jobs SQL | 754 jobs PhD | 750 jobs

Top 20 Job Perks/Benefits for Senior-level / Expert Machine Learning Engineer roles

The three most common job benefits and perks assiciated with senior-level / expert 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 | 2960 jobs Health care | 1753 jobs Equity / stock options | 1500 jobs Flex vacation | 1088 jobs Flex hours | 1058 jobs Salary bonus | 1031 jobs Parental leave | 891 jobs Startup environment | 880 jobs Competitive pay | 879 jobs Medical leave | 795 jobs Insurance | 790 jobs Team events | 577 jobs 401(k) matching | 561 jobs Conferences | 441 jobs Flexible spending account | 395 jobs Wellness | 378 jobs Home office stipend | 348 jobs Transparency | 187 jobs Relocation support | 156 jobs Gear | 117 jobs

Salary Composition for Senior-Level Machine Learning Engineers in Germany

The salary for a Senior-Level Machine Learning Engineer in Germany typically comprises several components. The fixed base salary is the most significant portion, often accounting for 70-80% of the total compensation package. This base salary can vary depending on the region, with cities like Berlin and Munich generally offering higher salaries due to the higher cost of living and concentration of tech companies.

In addition to the base salary, bonuses are a common component, usually making up 10-20% of the total compensation. These bonuses can be performance-based, tied to individual, team, or company performance metrics. Some companies, especially larger tech firms or those in competitive industries like finance or automotive, may offer additional remuneration in the form of stock options or equity, which can be a significant part of the compensation package, particularly in startups or high-growth companies.

Steps to Increase Salary from a Senior-Level Position

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

  • Specialization: Develop expertise in a niche area of machine learning, such as natural language processing, computer vision, or reinforcement learning. Specialized skills can command higher salaries.
  • Leadership Roles: Transition into leadership or managerial roles, such as a Machine Learning Team Lead or Director of AI, which typically offer higher compensation.
  • Continuous Learning: Stay updated with the latest advancements in AI/ML through courses, workshops, and conferences. This not only enhances your skills but also increases your value to employers.
  • Networking: Build a strong professional network within the AI/ML community. Networking can lead to opportunities in higher-paying roles or companies.
  • Negotiation Skills: Improve your negotiation skills to better advocate for higher compensation during job offers or performance reviews.

Educational Requirements for Senior-Level Machine Learning Engineers

Most senior-level machine learning positions require at least a master's degree in a relevant field such as computer science, data science, mathematics, or statistics. A Ph.D. is often preferred, especially for roles that involve research or developing new algorithms. The educational background should include a strong foundation in machine learning, data analysis, and programming.

Helpful Certifications for Machine Learning Engineers

While not always mandatory, certain certifications can enhance your credentials and demonstrate expertise to potential employers. Some valuable certifications include:

  • Google Professional Machine Learning Engineer: Validates your ability to design, build, and productionize ML models on Google Cloud.
  • AWS Certified Machine Learning – Specialty: Demonstrates your expertise in building, training, tuning, and deploying machine learning models on AWS.
  • Microsoft Certified: Azure AI Engineer Associate: Focuses on using Azure services to build and deploy AI solutions.

Experience Required for Senior-Level Roles

Typically, a senior-level machine learning engineer is expected to have 5-10 years of experience in the field. This experience should include hands-on work with machine learning models, data analysis, and software development. Experience in leading projects or teams, as well as a proven track record of successful machine learning implementations, is highly valued.

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