Salary for Entry-level / Junior Research Engineer during 2024

Salary details

The average entry-level / junior Research Engineer salary lies between USD 120,016 and USD 180,000 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, Machine Learning and Engineering. 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 | 131 jobs Machine Learning | 94 jobs Engineering | 86 jobs Python | 77 jobs Computer Science | 66 jobs PhD | 55 jobs Deep Learning | 49 jobs PyTorch | 39 jobs LLMs | 36 jobs Computer Vision | 33 jobs Privacy | 33 jobs Architecture | 31 jobs NeurIPS | 29 jobs R | 28 jobs TensorFlow | 28 jobs ML models | 24 jobs Mathematics | 24 jobs Open Source | 23 jobs Statistics | 22 jobs Industrial | 21 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, Conferences and Health care. 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 | 97 jobs Conferences | 43 jobs Health care | 41 jobs Startup environment | 32 jobs Team events | 30 jobs Flex hours | 28 jobs Equity / stock options | 23 jobs Medical leave | 22 jobs Parental leave | 19 jobs Insurance | 19 jobs Competitive pay | 17 jobs Flex vacation | 13 jobs Wellness | 11 jobs 401(k) matching | 9 jobs Salary bonus | 9 jobs Lunch / meals | 7 jobs Relocation support | 6 jobs Snacks / Drinks | 6 jobs Transparency | 4 jobs Flexible spending account | 4 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 10% to 20% of the base salary. Additional remuneration might include stock options, especially in tech companies or startups, which can be a significant part of the compensation in high-growth regions like Silicon Valley. In larger companies, benefits such as health insurance, retirement plans, and educational reimbursements are also common. The composition can vary by region, with tech hubs offering higher base salaries and more lucrative stock options, while smaller companies might offer lower base salaries but higher potential bonuses.

Steps to Increase Salary

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

• Skill Enhancement: Continuously update your skills in the latest AI/ML technologies and tools. Specializing in high-demand areas like deep learning, natural language processing, or computer vision can make you more valuable.
• Advanced Education: Pursuing a master's or Ph.D. in a relevant field can open up higher-paying opportunities and roles with more responsibility.
• Networking: Build a strong professional network by attending industry conferences, joining AI/ML communities, and engaging in online forums. Networking can lead to job opportunities with better compensation.
• Performance Excellence: Consistently exceed performance expectations in your current role to position yourself for promotions and salary increases.
• Certifications: Obtain relevant certifications that can validate your expertise and potentially lead to higher-paying roles.

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. However, a master's degree is increasingly preferred, especially for roles that involve research and development. Coursework in machine learning, data analysis, programming, and statistics is essential. Some positions may also require knowledge of specific programming languages such as Python, R, or Java, and familiarity with machine learning frameworks like TensorFlow or PyTorch.

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 provide a competitive edge and may lead to better job opportunities and higher salaries.

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. Experience with data analysis, machine learning model development, and programming is often required. Demonstrating experience through a portfolio of projects or contributions to open-source projects can be beneficial. While direct industry experience may not be mandatory, familiarity with the tools and processes used in AI/ML is crucial.

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