Salary for Mid-level / Intermediate Machine Learning Platform Engineer during 2024

Salary details

The average mid-level / intermediate Machine Learning Platform Engineer salary lies between USD 150,000 and USD 233,840 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. 22, 2024

Top 20 Job Tags for Mid-level / Intermediate Machine Learning Platform Engineer roles

The three most common job tag items assiciated with mid-level / intermediate Machine Learning Platform Engineer job listings are Machine Learning, Python and Distributed Systems. 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 | 5 jobs Python | 4 jobs Distributed Systems | 4 jobs Linux | 3 jobs Research | 3 jobs Computer Science | 3 jobs TensorFlow | 2 jobs PyTorch | 2 jobs GPU | 2 jobs Engineering | 2 jobs CUDA | 2 jobs HPC | 2 jobs Mathematics | 2 jobs Deep Learning | 1 jobs NLP | 1 jobs Big Data | 1 jobs AWS | 1 jobs Rust | 1 jobs Testing | 1 jobs GCP | 1 jobs

Top 20 Job Perks/Benefits for Mid-level / Intermediate Machine Learning Platform Engineer roles

The three most common job benefits and perks assiciated with mid-level / intermediate Machine Learning Platform Engineer job listings are Career development, Health care and Lunch / meals. 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 | 5 jobs Health care | 3 jobs Lunch / meals | 2 jobs Wellness | 2 jobs Team events | 2 jobs Salary bonus | 2 jobs Equity / stock options | 1 jobs Flex hours | 1 jobs Flex vacation | 1 jobs Startup environment | 1 jobs Unlimited paid time off | 1 jobs

Salary Composition

The salary for a Mid-level/Intermediate Machine Learning Platform Engineer typically comprises several components: a fixed base salary, performance-based bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The fixed base salary is often the largest portion, accounting for 70-80% of the total compensation package. Bonuses can vary significantly depending on the company's performance and individual contributions, usually ranging from 10-20%. Additional remuneration, like stock options, is more common in larger tech companies or startups and can make up 10-15% of the total package. Regional differences also play a role; for instance, salaries in tech hubs like Silicon Valley or New York City tend to be higher due to the cost of living and competitive job market. Industry-wise, tech companies, financial services, and healthcare often offer higher compensation compared to other sectors.

Increasing Salary

To increase your salary from this position, consider the following strategies:

• Skill Enhancement: Continuously update your skills in emerging technologies and tools in AI/ML, such as deep learning frameworks, cloud platforms, and data engineering tools.
• Advanced Education: Pursuing a master's degree or Ph.D. in a related field can open doors to higher-paying roles.
• Leadership Roles: Transitioning into a leadership or managerial role can significantly boost your salary.
• Networking: Building a strong professional network can lead to opportunities in higher-paying companies or industries.
• Certifications: Obtaining advanced certifications can demonstrate expertise and justify a higher salary.

Educational Requirements

Most mid-level 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 is often preferred and can be a significant advantage. Courses in machine learning, statistics, data structures, algorithms, and software engineering are particularly relevant. Some roles may also require knowledge of specific programming languages like Python, R, or Java.

Helpful Certifications

While not always mandatory, certain certifications can enhance your profile and demonstrate your expertise:

• Certified Machine Learning Professional (CMLP)
• AWS Certified Machine Learning – Specialty
• Google Professional Machine Learning Engineer
• Microsoft Certified: Azure AI Engineer Associate

These certifications can validate your skills in specific platforms and tools, making you more attractive to potential employers.

Required Experience

Typically, a mid-level machine learning platform 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 cloud platforms, big data technologies, and deploying machine learning models in production environments is highly valued. Additionally, experience in cross-functional teams and projects can be beneficial.

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