Machine Learning Model Engineer Salary in United States during 2024

Salary details

The average Machine Learning Model Engineer salary lies between USD 230,000 and USD 280,000 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 Model Engineer roles

The three most common job tag items assiciated with Machine Learning Model Engineer job listings are Python, Machine Learning and TensorFlow. 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:

Python | 23 jobs Machine Learning | 23 jobs TensorFlow | 23 jobs PyTorch | 23 jobs PhD | 23 jobs Computer Science | 23 jobs Privacy | 23 jobs Big Data | 22 jobs Kafka | 22 jobs Spark | 22 jobs AWS | 22 jobs Research | 22 jobs Data Mining | 22 jobs Engineering | 22 jobs Flink | 22 jobs NeurIPS | 22 jobs ICML | 22 jobs OOP | 22 jobs SQL | 19 jobs MLOps | 19 jobs

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

The three most common job benefits and perks assiciated with Machine Learning Model Engineer job listings are Career development, Health care and Insurance. 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 | 23 jobs Health care | 11 jobs Insurance | 10 jobs Equity / stock options | 1 jobs Competitive pay | 1 jobs Salary bonus | 1 jobs Fertility benefits | 1 jobs

Salary Composition for Machine Learning Model Engineers

In the United States, the salary for a Machine Learning Model Engineer typically comprises a base salary, bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary is often the largest component, accounting for approximately 70-80% of the total compensation package. Bonuses, which can be performance-based or company-wide, might contribute around 10-20%. Additional remuneration, such as stock options, can vary significantly depending on the company size and industry. For instance, tech giants and startups in Silicon Valley often offer substantial equity packages, whereas companies in other regions or industries might provide smaller or no equity. Larger companies might also offer more comprehensive benefits packages, including health insurance, retirement plans, and other perks, which can add significant value to the overall compensation.

Steps to Increase Salary Further

To increase your salary beyond the median of $230,000, consider the following strategies:

• Specialize in High-Demand Areas: Focus on niche areas within AI/ML, such as deep learning, natural language processing, or computer vision, which are in high demand and can command higher salaries.
• Pursue Leadership Roles: Transitioning into roles such as a lead engineer, team manager, or director 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 cutting-edge technologies can make you more valuable.
• Network and Build a Personal Brand: Attend industry conferences, contribute to open-source projects, and publish research to enhance your visibility and reputation in the field.
• Negotiate Offers: When switching jobs, negotiate your salary and benefits package effectively. Consider leveraging offers from multiple companies to maximize your compensation.

Educational Requirements

Most Machine Learning Model 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 or Ph.D. is often preferred, especially for roles involving complex model development and research. Advanced degrees provide a deeper understanding of machine learning algorithms, statistical methods, and data analysis, which are crucial for this role.

Helpful Certifications

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

• 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 specific platforms and tools, making you more competitive in the job market.

Required Experience

Typically, employers look for candidates with 3-5 years of experience in machine learning or data science roles. Experience in developing, deploying, and optimizing machine learning models is crucial. Familiarity with programming languages such as Python or R, and experience with machine learning frameworks like TensorFlow, PyTorch, or scikit-learn, are often required. Experience in handling large datasets and working with cloud platforms like AWS, Google Cloud, or Azure is also highly valued.

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