Salary for Entry-level / Junior Engineer during 2024

Salary details

The average entry-level / junior Engineer salary lies between USD 70,000 and USD 135,400 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: Dec. 15, 2024

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 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 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 jobs

Salary Composition

The salary for an entry-level or junior AI/ML/Data Science engineer typically consists of a base salary, 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. Bonuses can vary significantly depending on the company and industry; tech companies and startups might offer performance-based bonuses, while larger corporations may have more structured bonus plans. Additional remuneration can include stock options, especially in tech startups, or benefits like health insurance, retirement plans, and paid time off. The composition can also vary by region, with tech hubs like Silicon Valley offering higher base salaries and more lucrative stock options compared to other regions.

Increasing Salary

To increase your salary from an entry-level position, consider gaining specialized skills or certifications that are in high demand. Pursuing advanced education, such as a master's degree in a relevant field, can also be beneficial. Networking within the industry and seeking mentorship can provide insights into career advancement opportunities. Additionally, gaining experience in high-impact projects or transitioning to roles with more responsibility, such as a senior data scientist or machine learning engineer, can lead to salary increases. Staying updated with the latest trends and technologies in AI/ML can also make you more valuable to employers.

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 accept candidates with degrees in other fields if they have relevant experience or skills. A strong foundation in programming, data analysis, and machine learning concepts is essential. While a bachelor's degree is often sufficient for entry-level roles, a master's degree can be advantageous and may be required for more advanced positions.

Helpful Certifications

Certifications can enhance your resume and demonstrate your expertise to potential employers. Some popular certifications in the AI/ML/Data Science field 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 validate your skills in specific tools and platforms, making you more competitive in the job market.

Required Experience

For entry-level positions, employers typically look for candidates with some practical experience, which can be gained through internships, projects, or coursework. Experience with programming languages such as Python or R, familiarity with machine learning frameworks like TensorFlow or PyTorch, and proficiency in data analysis tools are often expected. While direct work experience may not be required, demonstrating your ability to apply theoretical knowledge to real-world problems is crucial.

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