Salary for Entry-level / Junior Research Engineer in United States during 2024

Salary details

The average entry-level / junior Research Engineer salary lies between USD 118,400 and USD 176,239 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: Dec. 22, 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 | 145 jobs Machine Learning | 107 jobs Engineering | 94 jobs Python | 83 jobs Computer Science | 76 jobs PhD | 58 jobs Deep Learning | 56 jobs PyTorch | 48 jobs LLMs | 46 jobs Computer Vision | 36 jobs TensorFlow | 35 jobs Privacy | 35 jobs Architecture | 34 jobs NeurIPS | 33 jobs R | 29 jobs Open Source | 29 jobs ML models | 26 jobs NLP | 24 jobs Mathematics | 24 jobs Industrial | 22 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 | 105 jobs Conferences | 52 jobs Health care | 44 jobs Team events | 38 jobs Startup environment | 34 jobs Flex hours | 33 jobs Medical leave | 24 jobs Equity / stock options | 23 jobs Insurance | 20 jobs Parental leave | 19 jobs Competitive pay | 18 jobs Flex vacation | 15 jobs 401(k) matching | 11 jobs Wellness | 11 jobs Salary bonus | 10 jobs Lunch / meals | 7 jobs Relocation support | 6 jobs Snacks / Drinks | 6 jobs Transparency | 5 jobs Flexible spending account | 5 jobs

Salary Composition

In the United States, the salary composition for an entry-level or junior research engineer in AI/ML/Data Science typically includes a base salary, performance bonuses, and sometimes additional remuneration such as stock options or equity, especially in tech companies. The base salary is the fixed component and usually constitutes the majority of the total compensation package. Performance bonuses can vary significantly depending on the company’s policies and your individual performance.

• Region: Salaries can vary by region, with tech hubs like San Francisco, New York, and Seattle offering higher base salaries to account for the higher cost of living.
• Industry: Industries such as finance, healthcare, and technology tend to offer higher compensation packages compared to academia or non-profit sectors.
• Company Size: Larger companies often provide more comprehensive compensation packages, including bonuses and stock options, while startups might offer lower base salaries but compensate with equity.

Increasing Salary

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

• Skill Development: Continuously update and expand your skill set, focusing on in-demand technologies and tools in AI/ML.
• Advanced Education: Pursuing a master's or Ph.D. in a relevant field can open up higher-paying opportunities.
• Networking: Build a strong professional network to learn about new opportunities and gain insights into industry trends.
• Performance: Consistently exceed performance expectations to position yourself for promotions and salary increases.
• Specialization: Develop expertise in a niche area of AI/ML that is in high demand, such as natural language processing or computer vision.

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, a master's degree is often preferred and can make candidates more competitive. Coursework in machine learning, statistics, and programming is essential.

Helpful Certificates

While not always required, certain certifications can enhance your resume and demonstrate your commitment to the field:

• Certified Machine Learning Specialist (CMLS)
• TensorFlow Developer Certificate
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate

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

Experience Requirements

For entry-level roles, employers typically look for candidates with some practical experience, which can be gained through internships, co-op programs, or relevant projects. Experience with programming languages like Python or R, and familiarity with machine learning frameworks such as TensorFlow or PyTorch, is often expected.

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