Machine Learning Model Engineer Salary in 2024

Salary details

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

The salary for a Machine Learning Model 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 tech hubs like Silicon Valley, the base salary might be higher, but the cost of living is also elevated. In contrast, companies in regions with a lower cost of living might offer a smaller base salary but compensate with substantial bonuses or stock options. In large tech companies, equity can form a significant part of the total compensation package, while smaller startups might offer more in terms of equity to attract talent. Industries like finance or healthcare might offer higher bonuses due to the critical nature of AI applications in those fields.

Steps to Increase Salary from This Position

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

• Specialization: Develop expertise in a niche area of machine learning, such as deep learning, natural language processing, or computer vision, which can make you more valuable.
• Leadership Roles: Transition into roles that involve leading teams or projects, such as a Machine Learning Team Lead or Manager.
• Continuous Learning: Stay updated with the latest advancements in AI/ML through courses, workshops, and conferences.
• Networking: Build a strong professional network to learn about higher-paying opportunities and gain insights into industry trends.
• Negotiation Skills: Improve your negotiation skills to better advocate for higher compensation during performance reviews or when switching jobs.

Educational Requirements

Most Machine Learning Model Engineer positions require at least a bachelor's degree in computer science, data science, mathematics, or a related field. However, a master's degree or Ph.D. is often preferred, especially for roles that involve complex problem-solving and research. Advanced degrees can provide a deeper understanding of machine learning algorithms and statistical methods, which are crucial for developing sophisticated models.

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 can validate your skills in specific platforms and tools, making you more attractive to employers who use these technologies.

Required Experience

Typically, employers look for candidates with at least 3-5 years of experience in machine learning or data science roles. Experience in developing and deploying machine learning models, working with large datasets, and using programming languages like Python or R is crucial. Experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn is also highly valued. Additionally, experience in a specific industry can be beneficial, as it provides context for applying machine learning solutions effectively.

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