Salary for Senior-level / Expert Machine Learning Engineer during 2023

Salary details

The average senior-level / expert Machine Learning Engineer salary lies between USD 150,000 and USD 238,000 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

Salary trend

Top 20 Job Tags for Senior-level / Expert Machine Learning Engineer roles

The three most common job tag items assiciated with senior-level / expert Machine Learning Engineer job listings are Machine Learning, Python and Engineering. Below you find a list of the 20 most occuring job tags in 2023 and the number of open jobs that where associated with them during that period:

Machine Learning | 1268 jobs Python | 1050 jobs Engineering | 998 jobs ML models | 747 jobs Computer Science | 735 jobs PyTorch | 611 jobs TensorFlow | 554 jobs Deep Learning | 528 jobs Research | 510 jobs Pipelines | 508 jobs AWS | 452 jobs NLP | 431 jobs Testing | 398 jobs Statistics | 398 jobs Architecture | 378 jobs Java | 361 jobs Spark | 322 jobs Mathematics | 317 jobs SQL | 311 jobs PhD | 306 jobs

Top 20 Job Perks/Benefits for Senior-level / Expert Machine Learning Engineer roles

The three most common job benefits and perks assiciated with senior-level / expert Machine Learning Engineer job listings are Career development, Health care and Equity / stock options. Below you find a list of the 20 most occuring job perks or benefits in 2023 and the number of open jobs that where offering them during that period:

Career development | 1072 jobs Health care | 562 jobs Equity / stock options | 499 jobs Flex hours | 465 jobs Flex vacation | 407 jobs Salary bonus | 390 jobs Startup environment | 345 jobs Parental leave | 321 jobs Competitive pay | 283 jobs Medical leave | 268 jobs Insurance | 267 jobs Team events | 250 jobs Wellness | 209 jobs 401(k) matching | 160 jobs Home office stipend | 149 jobs Unlimited paid time off | 82 jobs Signing bonus | 74 jobs Flexible spending account | 72 jobs Conferences | 64 jobs Relocation support | 61 jobs

Salary Composition for Senior-Level/Expert Machine Learning Engineer

The salary for a Senior-Level or Expert Machine Learning 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 composition can vary significantly depending on the region, industry, and company size.

• Region: In tech hubs like Silicon Valley, New York, or Seattle, the base salary tends to be higher due to the cost of living and competition for talent. In contrast, regions with a lower cost of living might offer a lower base salary but compensate with other benefits.
• Industry: Industries such as finance, healthcare, and technology often offer higher salaries due to the critical nature of AI/ML applications in these fields.
• Company Size: Larger companies may offer more comprehensive compensation packages, including bonuses and stock options, while startups might offer lower base salaries but higher equity stakes.

Steps to Increase Salary from This Position

To increase your salary further from a Senior-Level/Expert Machine Learning Engineer position, 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.
• Leadership Roles: Transition into leadership roles such as AI/ML team lead or manager, which often come with higher compensation.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML to maintain a competitive edge.
• Networking and Visibility: Attend industry conferences, contribute to open-source projects, and publish research to increase your visibility and network within the industry.
• Negotiation Skills: Improve your negotiation skills to better advocate for higher compensation during performance reviews or when switching jobs.

Educational Requirements

Most Senior-Level/Expert Machine Learning Engineer positions require at least a master's degree in a relevant field such as computer science, data science, statistics, or electrical engineering. A Ph.D. is often preferred, especially for roles that involve research and development of new algorithms or technologies.

Helpful Certifications

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

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

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

Required Experience

Typically, a Senior-Level/Expert Machine Learning Engineer is expected to have at least 5-10 years of experience in the field. This experience should include:

• Hands-on experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, or Scikit-learn.
• Proven track record of deploying machine learning models in production environments.
• Experience in data preprocessing, feature engineering, and model evaluation.
• A history of working on complex projects that demonstrate problem-solving skills and technical expertise.

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