Research Engineer Salary in United States during 2024

Salary details

The average Research Engineer salary lies between USD 144,600 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 Research Engineer roles

The three most common job tag items assiciated with 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 | 1142 jobs Engineering | 865 jobs Machine Learning | 823 jobs Python | 757 jobs Computer Science | 618 jobs PyTorch | 445 jobs PhD | 395 jobs Deep Learning | 391 jobs LLMs | 331 jobs Architecture | 315 jobs TensorFlow | 312 jobs NLP | 267 jobs Security | 245 jobs ML models | 237 jobs Statistics | 231 jobs Testing | 230 jobs Computer Vision | 220 jobs R | 219 jobs Privacy | 215 jobs Pipelines | 211 jobs

Top 20 Job Perks/Benefits for Research Engineer roles

The three most common job benefits and perks assiciated with 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 | 871 jobs Health care | 476 jobs Equity / stock options | 382 jobs Conferences | 251 jobs Flex hours | 249 jobs Startup environment | 243 jobs Competitive pay | 204 jobs Flex vacation | 201 jobs Salary bonus | 197 jobs Insurance | 175 jobs Parental leave | 170 jobs Medical leave | 165 jobs Team events | 162 jobs Relocation support | 141 jobs 401(k) matching | 116 jobs Wellness | 80 jobs Unlimited paid time off | 62 jobs Flexible spending account | 41 jobs Lunch / meals | 39 jobs Home office stipend | 37 jobs

Salary Composition

The salary for a Research Engineer in AI/ML/Data Science typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. 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 and individual achievements. In tech hubs like Silicon Valley, equity or stock options are common, providing long-term incentives. In contrast, companies in other regions might offer higher cash bonuses instead. Larger companies often have more structured bonus and equity programs, while startups might offer more equity to compensate for lower base salaries.

Steps to Increase Salary

To increase your salary from this position, consider pursuing advanced roles such as Senior Research Engineer or transitioning into management positions like AI/ML Team Lead. Specializing in high-demand areas such as deep learning, natural language processing, or computer vision can also enhance your value. Additionally, contributing to high-impact projects, publishing research papers, and obtaining patents can significantly boost your profile. Networking within the industry and attending conferences can open up opportunities for higher-paying roles. Finally, consider negotiating your salary during performance reviews or when taking on additional responsibilities.

Educational Requirements

Most Research Engineer positions in AI/ML/Data Science require at least a Master's degree in a related field such as Computer Science, Data Science, or Electrical Engineering. A Ph.D. is often preferred, especially for roles focused on cutting-edge research and development. These educational programs provide a strong foundation in algorithms, statistics, and machine learning principles, which are crucial for success in this field. Additionally, coursework in mathematics, data analysis, and programming languages like Python and R is highly beneficial.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credentials and demonstrate expertise. Certifications such as the TensorFlow Developer Certificate, AWS Certified Machine Learning – Specialty, and Microsoft Certified: Azure AI Engineer Associate are well-regarded in the industry. These certifications validate your skills in specific tools and platforms, making you more attractive to potential employers. Additionally, completing online courses from platforms like Coursera, edX, or Udacity in specialized AI/ML topics can further bolster your qualifications.

Required Experience

Typically, a Research Engineer role requires 3-5 years of experience in AI/ML or related fields. This experience should include hands-on work with machine learning models, data analysis, and software development. Experience in research environments, such as academic labs or R&D departments, is highly valued. Familiarity with industry-standard tools and frameworks like TensorFlow, PyTorch, and Scikit-learn is often expected. Additionally, experience in deploying machine learning models in production environments can be a significant advantage.

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