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

Salary details

The average entry-level / junior Engineer salary lies between USD 70,950 and USD 142,000 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: Jan. 19, 2025

Top 20 Job Tags for Entry-level / Junior Engineer roles

The three most common job tag items assiciated with entry-level / junior Engineer job listings are Python, Engineering and Machine Learning. 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:

Python | 4029 jobs Engineering | 3898 jobs Machine Learning | 2862 jobs Computer Science | 2715 jobs SQL | 2048 jobs Research | 1567 jobs Pipelines | 1403 jobs AWS | 1198 jobs Architecture | 1160 jobs Testing | 1134 jobs Java | 1118 jobs Azure | 1020 jobs Security | 989 jobs Statistics | 930 jobs Big Data | 903 jobs Agile | 902 jobs ETL | 862 jobs Mathematics | 851 jobs Spark | 798 jobs R | 755 jobs

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

The three most common job benefits and perks assiciated with entry-level / junior Engineer job listings are Career development, Health care and Flex hours. 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 | 3487 jobs Health care | 1419 jobs Flex hours | 1102 jobs Startup environment | 1096 jobs Team events | 1083 jobs Equity / stock options | 997 jobs Competitive pay | 797 jobs Medical leave | 765 jobs Insurance | 740 jobs Flex vacation | 637 jobs Parental leave | 510 jobs Salary bonus | 471 jobs 401(k) matching | 383 jobs Conferences | 344 jobs Wellness | 278 jobs Flexible spending account | 229 jobs Relocation support | 219 jobs Fitness / gym | 183 jobs Transparency | 169 jobs Gear | 125 jobs

Salary Composition

In the United States, the salary composition for an entry-level or junior AI/ML/Data Science engineer typically includes a base salary, performance bonuses, and sometimes additional remuneration such as stock options or profit-sharing. 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 policy and individual performance, often ranging from 5% to 15% of the base salary. Additional remuneration like stock options is more common in tech companies, especially startups or large tech firms, and can be a significant part of the compensation in regions like Silicon Valley. In contrast, companies in other regions or industries might offer less in terms of stock options but could provide other benefits like health insurance, retirement plans, and educational reimbursements.

Increasing Salary

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

• Skill Enhancement: Continuously upgrade your technical skills, especially in high-demand areas like deep learning, natural language processing, or big data technologies.
• Advanced Education: Pursuing a master's degree or specialized certifications can make you more competitive.
• Networking: Build a strong professional network through industry conferences, meetups, and online platforms like LinkedIn.
• Performance Excellence: Consistently exceed performance expectations to position yourself for promotions and raises.
• Industry Switch: Consider moving to industries that pay higher salaries for AI/ML roles, such as finance or healthcare.

Educational Requirements

Most entry-level AI/ML/Data Science positions require at least a bachelor's degree in a related field such as computer science, data science, mathematics, or statistics. Some roles may prefer candidates with a master's degree, especially in competitive markets or for positions that require more specialized knowledge. Coursework in machine learning, data analysis, and programming is often essential.

Helpful Certifications

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

• Certified Data Scientist (CDS)
• TensorFlow Developer Certificate
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate
• Google Professional Machine Learning Engineer

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

Experience Requirements

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 models, and programming languages like Python or R is often expected. Demonstrating experience through a portfolio of projects or contributions to open-source projects can also be beneficial.

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