Salary for Senior-level / Expert Research Engineer in United States during 2024

Salary details

The average senior-level / expert Research Engineer salary lies between USD 150,000 and USD 251,000 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. 24, 2024

Salary trend

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

The three most common job tag items assiciated with senior-level / expert Research Engineer job listings are Research, Engineering and Machine Learning. 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:

Research | 532 jobs Engineering | 410 jobs Machine Learning | 402 jobs Python | 383 jobs Computer Science | 315 jobs PyTorch | 216 jobs LLMs | 182 jobs Deep Learning | 179 jobs Architecture | 178 jobs PhD | 169 jobs TensorFlow | 157 jobs NLP | 136 jobs ML models | 128 jobs Testing | 123 jobs Pipelines | 112 jobs Security | 110 jobs Privacy | 110 jobs Generative AI | 105 jobs R | 100 jobs Statistics | 100 jobs

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

The three most common job benefits and perks assiciated with senior-level / expert Research 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 2024 and the number of open jobs that where offering them during that period:

Career development | 429 jobs Health care | 226 jobs Equity / stock options | 206 jobs Salary bonus | 124 jobs Flex hours | 123 jobs Startup environment | 123 jobs Flex vacation | 110 jobs Competitive pay | 96 jobs Conferences | 93 jobs Insurance | 90 jobs Parental leave | 87 jobs Medical leave | 87 jobs Team events | 71 jobs 401(k) matching | 62 jobs Relocation support | 62 jobs Wellness | 37 jobs Unlimited paid time off | 33 jobs Lunch / meals | 23 jobs Home office stipend | 23 jobs Flexible spending account | 23 jobs

Salary Composition

In the United States, the salary composition for a Senior-level or Expert Research Engineer in AI/ML/Data Science typically includes a combination of a fixed base salary, performance-based bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary often constitutes the majority of the total compensation package, ranging from 60% to 80%. Bonuses can vary significantly depending on the company and industry, often ranging from 10% to 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% to 30% of the total compensation. The exact composition can vary based on the region, with tech hubs like Silicon Valley offering higher equity components, while other regions might focus more on cash compensation. Similarly, larger companies might offer more structured bonus plans, whereas smaller companies might provide more equity.

Increasing Salary Further

To increase your salary further from this position, consider the following strategies:

• Specialization: Develop expertise in a niche area of AI/ML that is in high demand but has a limited supply of experts, such as reinforcement learning or AI ethics.
• Leadership Roles: Transition into leadership or managerial roles, such as a Director of AI or Chief Data Scientist, which typically offer higher compensation.
• Continuous Learning: Stay updated with the latest advancements in AI/ML through courses, workshops, and conferences, which can make you more valuable to your employer.
• Networking: Build a strong professional network to learn about higher-paying opportunities and gain insights into industry trends.
• Consulting: Consider offering consulting services on the side, which can significantly boost your income.

Educational Requirements

For a Senior-level or Expert Research Engineer position in AI/ML/Data Science, a strong educational background is typically required. Most candidates hold 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 research-intensive roles, as it demonstrates a deep understanding of complex concepts and the ability to conduct independent research. Additionally, a solid foundation in mathematics, particularly in areas like linear algebra, calculus, and probability, is essential.

Helpful Certificates

While not always mandatory, certain certifications can enhance your profile and demonstrate your commitment to the field. Some valuable certifications include:

• Certified Machine Learning Professional (CMLP)
• TensorFlow Developer Certificate
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate
• Data Science Council of America (DASCA) Senior Data Scientist (SDS) Certification

These certifications can help validate your skills and knowledge, making you a more attractive candidate to potential employers.

Required Experience

Typically, a Senior-level or Expert Research Engineer in AI/ML/Data Science is expected to have at least 5 to 10 years of relevant experience. This experience should include hands-on work with machine learning models, data analysis, and software development. Experience in leading projects, mentoring junior engineers, and contributing to research publications can also be highly beneficial. Additionally, familiarity with industry-standard tools and platforms, such as Python, R, TensorFlow, PyTorch, and cloud services like AWS or Azure, is often required.

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