Salary for Entry-level / Junior Research Engineer during 2023

Salary details

The average entry-level / junior Research Engineer salary lies between USD 98,000 and USD 160,000 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. 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 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 success and individual performance, often ranging from 5% to 20% of the base salary. 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 offering higher base salaries and stock options, while other regions might offer more balanced packages. Industry and company size also play a role; larger companies might offer more comprehensive benefits, while startups might compensate with equity.

Increasing Salary

To increase your salary from an entry-level position, consider gaining specialized skills or certifications that are in high demand, such as deep learning, natural language processing, or cloud computing. Pursuing a master's degree or Ph.D. in a related field can also enhance your qualifications and open up opportunities for higher-level positions. Networking within the industry and attending conferences can help you stay updated on trends and connect with potential employers. Additionally, gaining experience in managing projects or leading teams can position you for roles with greater responsibility and higher pay.

Educational Requirements

Most entry-level positions in AI/ML/Data Science require at least a bachelor's degree in computer science, data science, mathematics, statistics, or a related field. A strong foundation in programming languages such as Python or R, as well as knowledge of machine learning algorithms and data analysis techniques, is essential. Some positions may prefer candidates with a master's degree, especially for roles that involve more complex research or development tasks.

Helpful Certifications

While not always required, certain certifications can enhance your resume and demonstrate your expertise. Popular certifications include:

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

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

Required Experience

For entry-level roles, employers typically look for candidates with some practical experience, which can be gained through internships, co-op programs, or personal projects. Experience with data manipulation, machine learning libraries (such as TensorFlow, PyTorch, or scikit-learn), and data visualization tools is often expected. Demonstrating your ability to work on real-world problems and contribute to projects can be a significant advantage.

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