Salary for Mid-level / Intermediate Research Engineer in United States during 2023

Salary details

The average mid-level / intermediate Research Engineer salary lies between USD 100,000 and USD 200,000 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 Mid-level / Intermediate Research Engineer roles

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

Research | 50 jobs Engineering | 36 jobs Machine Learning | 34 jobs Python | 33 jobs Computer Science | 27 jobs PhD | 19 jobs Architecture | 16 jobs Security | 15 jobs PyTorch | 14 jobs Testing | 14 jobs TensorFlow | 12 jobs Java | 9 jobs R | 8 jobs Linux | 8 jobs Agile | 8 jobs R&D | 8 jobs Deep Learning | 7 jobs NLP | 7 jobs AWS | 7 jobs ML models | 7 jobs

Top 20 Job Perks/Benefits for Mid-level / Intermediate Research Engineer roles

The three most common job benefits and perks assiciated with mid-level / intermediate Research Engineer job listings are Career development, Health care and Competitive pay. 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 | 42 jobs Health care | 26 jobs Competitive pay | 20 jobs Flex vacation | 16 jobs Equity / stock options | 15 jobs Flex hours | 14 jobs Startup environment | 14 jobs Conferences | 12 jobs Team events | 12 jobs Insurance | 9 jobs Salary bonus | 9 jobs Medical leave | 7 jobs 401(k) matching | 6 jobs Parental leave | 6 jobs Unlimited paid time off | 5 jobs Wellness | 3 jobs Home office stipend | 2 jobs Flat hierarchy | 1 jobs Gear | 1 jobs Fitness / gym | 1 jobs

Salary Composition

The salary for a Mid-level/Intermediate Research Engineer in AI/ML/Data Science typically comprises several components. The fixed base salary is the primary component, often making up the majority of the total compensation package. Bonuses, which can be performance-based or tied to company success, are another significant part. These bonuses can vary widely depending on the company size, industry, and region. For instance, tech giants in Silicon Valley might offer substantial bonuses compared to smaller startups or companies in other regions. Additional remuneration can include stock options, especially in tech companies, and benefits such as health insurance, retirement plans, and other perks. In regions with a high cost of living, such as New York or San Francisco, companies might offer higher base salaries to attract talent.

Increasing 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 or Director of Data Science. Gaining expertise in high-demand areas such as deep learning, natural language processing, or computer vision can also make you more valuable. Networking within the industry and attending conferences can open up opportunities for higher-paying roles. Additionally, negotiating your salary during performance reviews or when switching jobs can lead to significant increases.

Educational Requirements

Most mid-level positions in AI/ML/Data Science require at least a bachelor's degree in a related field such as Computer Science, Mathematics, Statistics, or Engineering. However, a master's degree or Ph.D. is often preferred, especially for research-focused roles. These advanced degrees provide a deeper understanding of complex algorithms and data analysis techniques, which are crucial for success in this field.

Helpful Certificates

While not always mandatory, certain certifications can enhance your credentials and demonstrate your expertise. Certifications from recognized institutions or platforms, such as the Certified Data Scientist (CDS) or TensorFlow Developer Certificate, can be beneficial. Additionally, completing specialized courses from platforms like Coursera, edX, or Udacity in machine learning, data science, or AI can also be advantageous.

Required Experience

Typically, a mid-level position requires 3-5 years of experience in AI/ML or data science roles. This experience should include hands-on work with machine learning models, data analysis, and programming in languages such as Python or R. Experience with data visualization tools and cloud platforms like AWS or Azure is also often required. Demonstrating a track record of successful projects and contributions to research or product development can be crucial.

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