Machine Learning Platform Engineer Salary in 2024

Salary details

The average Machine Learning Platform Engineer salary lies between USD 167,000 and USD 230,000 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.

All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.

Last updated: Dec. 15, 2024

Top 20 Job Tags for Machine Learning Platform Engineer roles

The three most common job tag items assiciated with Machine Learning Platform Engineer job listings are Machine Learning, Engineering and Python. 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 | 28 jobs Engineering | 22 jobs Python | 20 jobs Computer Science | 17 jobs Model training | 16 jobs Architecture | 13 jobs Java | 12 jobs Distributed Systems | 11 jobs Microservices | 10 jobs Deep Learning | 9 jobs Model deployment | 9 jobs E-commerce | 8 jobs Kubernetes | 7 jobs Security | 7 jobs ML models | 7 jobs Open Source | 6 jobs AWS | 6 jobs Banking | 6 jobs Azure | 6 jobs APIs | 6 jobs

Top 20 Job Perks/Benefits for Machine Learning Platform Engineer roles

The three most common job benefits and perks assiciated with Machine Learning Platform Engineer job listings are Career development, Equity / stock options and Flex hours. 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 | 26 jobs Equity / stock options | 19 jobs Flex hours | 15 jobs Health care | 13 jobs Team events | 13 jobs Parental leave | 8 jobs Flex vacation | 8 jobs Wellness | 8 jobs Medical leave | 8 jobs Competitive pay | 7 jobs Insurance | 7 jobs Salary bonus | 7 jobs Flexible spending account | 6 jobs Signing bonus | 4 jobs 401(k) matching | 3 jobs Startup environment | 3 jobs Unlimited paid time off | 3 jobs Lunch / meals | 2 jobs Home office stipend | 1 jobs Fertility benefits | 1 jobs

Salary Composition for Machine Learning Platform Engineers

The salary for a Machine Learning Platform Engineer typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The composition can vary significantly based on region, industry, and company size. In the United States, for instance, tech hubs like Silicon Valley or New York City often offer higher base salaries and more substantial equity packages compared to other regions. In Europe, cities like London and Berlin are known for competitive salaries, though they might offer less in terms of equity compared to the U.S. In terms of industry, tech companies and startups might provide more equity, while traditional industries like finance or healthcare might offer higher base salaries and bonuses. Larger companies often have structured bonus systems and more comprehensive benefits, whereas smaller companies might offer more flexibility and potential for rapid salary growth through equity.

Steps to Increase Salary from This Position

To increase your salary further from the position of a Machine Learning Platform Engineer, consider the following strategies:

• Skill Enhancement: Continuously update your skills in the latest AI/ML technologies and tools. Specializing in high-demand areas like deep learning, natural language processing, or cloud-based ML solutions can make you more valuable.
• Leadership Roles: Transition into leadership or managerial roles, such as a Machine Learning Team Lead or Engineering Manager, which typically come with higher compensation.
• Industry Switch: Consider moving to industries that pay higher for ML expertise, such as finance, healthcare, or autonomous systems.
• Networking and Visibility: Attend industry conferences, contribute to open-source projects, and publish your work to increase your visibility and network, which can lead to higher-paying opportunities.
• Negotiation: Improve your negotiation skills to better advocate for higher pay during performance reviews or when switching jobs.

Educational Requirements

Most Machine Learning Platform Engineer positions require at least a bachelor's degree in computer science, data science, engineering, or a related field. However, a master's degree or Ph.D. can be advantageous, especially for roles that involve research or advanced algorithm development. A strong foundation in mathematics, statistics, and programming is essential, and coursework in machine learning, data structures, and algorithms is highly beneficial.

Helpful Certifications

While not always mandatory, certain certifications can enhance your profile 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 deploying machine learning models on specific platforms and can be particularly useful if you are targeting roles in companies that use these technologies.

Experience Requirements

Typically, employers look for candidates with 3-5 years of experience in software engineering, data science, or a related field. Experience with machine learning frameworks (such as TensorFlow, PyTorch, or Scikit-learn), cloud platforms (like AWS, Google Cloud, or Azure), and data engineering tools is often required. Experience in deploying and maintaining machine learning models in production environments is highly valued.

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