Machine Learning Modeler Salary in 2024

Salary details

The average Machine Learning Modeler salary lies between USD 139,000 and USD 245,400 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 Modeler roles

The three most common job tag items assiciated with Machine Learning Modeler job listings are Machine Learning, Open Source 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 | 9 jobs Open Source | 9 jobs Engineering | 9 jobs Banking | 9 jobs Crypto | 9 jobs Blockchain | 9 jobs Mathematics | 9 jobs Physics | 9 jobs Computer Science | 9 jobs Python | 8 jobs PyTorch | 8 jobs AWS | 8 jobs Airflow | 8 jobs Research | 8 jobs GCP | 8 jobs Classification | 8 jobs Snowflake | 8 jobs LLMs | 8 jobs Generative AI | 8 jobs Copilot | 8 jobs

Top 20 Job Perks/Benefits for Machine Learning Modeler roles

The three most common job benefits and perks assiciated with Machine Learning Modeler job listings are Career development, Equity / stock options and Parental leave. 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 | 9 jobs Equity / stock options | 8 jobs Parental leave | 8 jobs Wellness | 8 jobs Team events | 8 jobs Flex hours | 7 jobs Flex vacation | 7 jobs Health care | 7 jobs Signing bonus | 7 jobs Medical leave | 7 jobs Insurance | 7 jobs Salary bonus | 7 jobs Flexible spending account | 7 jobs Startup environment | 3 jobs

Salary Composition for a Machine Learning Modeler

The salary for a Machine Learning Modeler typically comprises a base salary, bonuses, and additional remuneration such as stock options or benefits. The base salary is the fixed component and usually forms the largest part of the total compensation package. Bonuses can vary significantly depending on the company's performance, individual performance, and industry standards. In tech-heavy regions like Silicon Valley, bonuses and stock options can be substantial, often making up a significant portion of the total compensation. In contrast, companies in regions with a lower cost of living or smaller tech hubs might offer smaller bonuses and fewer stock options. Additionally, larger companies or those in highly competitive industries may offer more lucrative compensation packages compared to smaller firms or those in less competitive sectors.

Steps to Increase Salary from This Position

To increase your salary from a Machine Learning Modeler position, consider the following strategies:

• Skill Enhancement: Continuously update and expand your skill set, particularly in emerging technologies and advanced machine learning techniques.
• Advanced Education: Pursue further education, such as a master's or Ph.D., which can open doors to higher-level positions.
• Networking: Build a strong professional network to learn about new opportunities and gain insights into industry trends.
• Leadership Roles: Aim for leadership or managerial roles within your organization, which typically come with higher pay.
• Industry Transition: Consider moving to industries that offer higher compensation for AI/ML roles, such as finance or healthcare.

Educational Requirements

Most Machine Learning Modeler positions require at least a bachelor's degree in a related field such as computer science, data science, mathematics, or engineering. However, a master's degree or Ph.D. is often preferred, especially for roles that involve complex problem-solving and research. These advanced degrees provide a deeper understanding of machine learning algorithms, statistical methods, and data analysis techniques, which are crucial for success in this field.

Helpful Certifications

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

• 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 a more attractive candidate.

Experience Requirements

Typically, employers look for candidates with at least 2-5 years of experience in machine learning or data science roles. This experience should include hands-on work with machine learning models, data analysis, and programming languages such as Python or R. Experience with machine learning frameworks like TensorFlow or PyTorch is also highly desirable. Additionally, experience in a specific industry can be beneficial, as it provides domain knowledge that can be crucial for developing effective models.

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