Machine Learning Platform Engineer Salary in United States during 2024

Salary details

The average Machine Learning Platform Engineer salary lies between USD 168,300 and USD 283,780 in the United States. 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.

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: Nov. 17, 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 | 26 jobs Engineering | 20 jobs Python | 19 jobs Computer Science | 16 jobs Model training | 15 jobs Architecture | 11 jobs Java | 11 jobs Distributed Systems | 10 jobs Deep Learning | 9 jobs Model deployment | 9 jobs Microservices | 9 jobs E-commerce | 8 jobs Security | 7 jobs Azure | 6 jobs ML models | 6 jobs APIs | 6 jobs Open Source | 5 jobs Kubernetes | 5 jobs AWS | 5 jobs Banking | 5 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 | 24 jobs Equity / stock options | 18 jobs Flex hours | 14 jobs Team events | 13 jobs Health care | 11 jobs Parental leave | 7 jobs Flex vacation | 7 jobs Wellness | 7 jobs Medical leave | 7 jobs Insurance | 7 jobs Salary bonus | 7 jobs Competitive pay | 5 jobs Flexible spending account | 5 jobs Signing bonus | 4 jobs 401(k) matching | 2 jobs Lunch / meals | 2 jobs Startup environment | 2 jobs Unlimited paid time off | 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 in the United States 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 base salary is often the largest portion, accounting for 60-80% of the total compensation package. Bonuses can vary significantly depending on the company’s performance and individual contributions, usually ranging from 10-20% of the base salary. Additional remuneration, such as stock options, can be a significant part of the package, particularly in startups or large tech firms, and may account for 10-20% or more of the total compensation. The exact composition can vary based on factors such as geographic location, with higher salaries often found in tech hubs like Silicon Valley, and industry, with finance and tech sectors typically offering more competitive packages. Company size also plays a role, with larger companies often providing more comprehensive benefits and stock options.

Steps to Increase Salary Further

To increase your salary beyond the median of USD 220,000, consider the following strategies:

• Specialize in High-Demand Areas: Focus on niche areas within AI/ML, such as deep learning, natural language processing, or reinforcement learning, which are in high demand and can command higher salaries.
• Pursue Leadership Roles: Transitioning into managerial or leadership positions, such as a Lead Machine Learning Engineer or an AI Team Manager, can significantly boost your earning potential.
• Continuous Learning and Upskilling: Stay updated with the latest technologies and methodologies in AI/ML. Advanced certifications or courses in emerging technologies can make you more valuable.
• Network and Build Industry Connections: Engage with professional networks and attend industry conferences to increase your visibility and open up opportunities for higher-paying roles.
• Negotiate Effectively: When offered a new position or during performance reviews, negotiate your salary and benefits package assertively.

Educational Requirements

Most Machine Learning Platform Engineer positions require at least a bachelor’s degree in a relevant field such as Computer Science, Data Science, Mathematics, or Engineering. However, a master’s degree or Ph.D. is often preferred, especially for roles involving complex algorithm development or research. Advanced degrees can provide a deeper understanding of machine learning theories and practices, making candidates more competitive.

Helpful Certifications

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

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

These certifications validate your skills in deploying machine learning models and working with cloud-based AI services, which are highly valued by employers.

Required Experience

Typically, employers look for candidates with 3-5 years of experience in machine learning or related fields. Experience in software engineering, data engineering, or data science is also beneficial. Practical experience with machine learning frameworks (such as TensorFlow, PyTorch, or Scikit-learn), programming languages (like Python or R), and cloud platforms (AWS, Google Cloud, Azure) is often required.

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