Salary for Entry-level / Junior Research Engineer in United States during 2023

Salary details

The average entry-level / junior Research Engineer salary lies between USD 120,000 and USD 160,000 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 Entry-level / Junior Research Engineer roles

The three most common job tag items assiciated with entry-level / junior Research Engineer job listings are Research, Engineering and Python. 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 | 88 jobs Engineering | 70 jobs Python | 47 jobs Machine Learning | 46 jobs Computer Science | 32 jobs Spark | 30 jobs PhD | 27 jobs Statistics | 26 jobs R | 23 jobs Matlab | 20 jobs Industrial | 20 jobs Privacy | 18 jobs Computer Vision | 16 jobs PyTorch | 16 jobs SQL | 14 jobs Deep Learning | 13 jobs Robotics | 13 jobs TensorFlow | 12 jobs Data Mining | 12 jobs Excel | 12 jobs

Top 20 Job Perks/Benefits for Entry-level / Junior Research Engineer roles

The three most common job benefits and perks assiciated with entry-level / junior Research Engineer job listings are Career development, Team events and Startup environment. 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 | 55 jobs Team events | 27 jobs Startup environment | 22 jobs Flex hours | 21 jobs Insurance | 20 jobs Equity / stock options | 18 jobs Conferences | 18 jobs Health care | 17 jobs Flex vacation | 11 jobs 401(k) matching | 8 jobs Wellness | 8 jobs Parental leave | 7 jobs Competitive pay | 6 jobs Medical leave | 6 jobs Relocation support | 4 jobs Snacks / Drinks | 4 jobs Salary bonus | 3 jobs Home office stipend | 2 jobs Lunch / meals | 1 jobs Travel | 1 jobs

Salary Composition

The salary for an entry-level or junior research engineer in AI/ML/Data Science typically consists of a base salary, performance bonuses, and sometimes additional remuneration such as stock options or benefits. The base salary is the fixed component and usually makes up the majority of the total compensation package. Performance bonuses can vary significantly depending on the company’s policies and your individual performance. Additional remuneration might include stock options, especially in tech companies or startups, and benefits like health insurance, retirement plans, and paid time off. The composition can vary by region, with tech hubs like Silicon Valley often offering higher base salaries and more substantial stock options. Industry also plays a role; for instance, finance and tech industries might offer higher bonuses compared to academia or non-profits. Company size can influence the package as well, with larger companies often providing more comprehensive benefits and smaller startups offering more equity.

Steps to Increase Salary

To increase your salary from an entry-level position, consider the following steps:

• Skill Enhancement: Continuously upgrade your skills in AI/ML through advanced courses or certifications. Specializing in high-demand areas like deep learning, natural language processing, or computer vision can make you more valuable.
• Networking: Build a strong professional network by attending industry conferences, meetups, and online forums. Networking can open up opportunities for higher-paying positions.
• Performance Excellence: Consistently exceed performance expectations in your current role. Demonstrating your impact on projects can position you for promotions or raises.
• Advanced Education: Pursuing a master’s or Ph.D. in a relevant field can lead to higher-level positions and salaries.
• Job Hopping: Sometimes, moving to a new company can result in a significant salary increase, especially if you have gained valuable experience and skills.

Educational Requirements

Most entry-level positions in AI/ML/Data Science require at least a bachelor’s degree in a related field such as computer science, data science, mathematics, or engineering. However, many employers prefer candidates with a master’s degree or even a Ph.D., especially for research-focused roles. A strong foundation in mathematics, statistics, and programming is essential, and coursework in machine learning, data analysis, and artificial intelligence is highly beneficial.

Helpful Certifications

While not always required, certain certifications can enhance your resume 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
• IBM Data Science Professional Certificate
• TensorFlow Developer Certificate

These certifications can validate your skills and knowledge in specific tools and platforms commonly used in the industry.

Required Experience

For entry-level positions, employers typically look for candidates with some practical experience, which can be gained through internships, co-op programs, or relevant projects during your studies. Experience with programming languages like Python or R, familiarity with machine learning frameworks such as TensorFlow or PyTorch, and hands-on experience with data analysis and visualization tools are often expected.

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