Salary for Entry-level / Junior Engineer during 2024

Salary details

The average entry-level / junior Engineer salary lies between USD 70,000 and USD 130,000 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. 10, 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 Computer Science. 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 | 3370 jobs Engineering | 3206 jobs Computer Science | 2297 jobs Machine Learning | 2251 jobs SQL | 1720 jobs Research | 1234 jobs Pipelines | 1144 jobs AWS | 991 jobs Java | 972 jobs Architecture | 964 jobs Testing | 950 jobs Azure | 846 jobs Security | 836 jobs Agile | 779 jobs Statistics | 764 jobs Big Data | 749 jobs Mathematics | 724 jobs ETL | 717 jobs Spark | 677 jobs R | 619 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 | 2828 jobs Health care | 1236 jobs Startup environment | 914 jobs Flex hours | 901 jobs Team events | 872 jobs Equity / stock options | 853 jobs Competitive pay | 685 jobs Medical leave | 683 jobs Insurance | 655 jobs Flex vacation | 551 jobs Parental leave | 448 jobs Salary bonus | 408 jobs 401(k) matching | 344 jobs Conferences | 280 jobs Wellness | 231 jobs Flexible spending account | 210 jobs Relocation support | 186 jobs Fitness / gym | 160 jobs Transparency | 148 jobs Gear | 109 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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