Salary for Entry-level / Junior Engineer in United States during 2024
π° The median Salary for Entry-level / Junior Engineer in United States during 2024 is USD 99,500
βοΈ This salary info is based on 218 individual salaries reported during 2024
Salary details
The average entry-level / junior Engineer salary lies between USD 74,652 and USD 143,100 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.
- Job title
- Engineer
- Experience
- Entry-level / Junior
- Region
- United States
- Salary year
- 2024
- Sample size
- 218
- Top 10%
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- Top 25%
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- Median
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- Bottom 25%
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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: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 | 3995 jobs Engineering | 3867 jobs Machine Learning | 2845 jobs Computer Science | 2696 jobs SQL | 2033 jobs Research | 1547 jobs Pipelines | 1386 jobs AWS | 1183 jobs Architecture | 1150 jobs Testing | 1130 jobs Java | 1123 jobs Azure | 1010 jobs Security | 991 jobs Statistics | 922 jobs Agile | 909 jobs Big Data | 895 jobs ETL | 855 jobs Mathematics | 841 jobs Spark | 788 jobs R | 747 jobsTop 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 Startup environment. 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 | 3466 jobs Health care | 1415 jobs Startup environment | 1090 jobs Team events | 1090 jobs Flex hours | 1088 jobs Equity / stock options | 990 jobs Competitive pay | 793 jobs Medical leave | 759 jobs Insurance | 736 jobs Flex vacation | 632 jobs Parental leave | 509 jobs Salary bonus | 466 jobs 401(k) matching | 381 jobs Conferences | 342 jobs Wellness | 282 jobs Flexible spending account | 229 jobs Relocation support | 214 jobs Fitness / gym | 180 jobs Transparency | 163 jobs Gear | 127 jobsSalary 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 companyβs 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 β 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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