Salary for Mid-level / Intermediate Engineer during 2024

Salary details

The average mid-level / intermediate Engineer salary lies between USD 100,000 and USD 180,000 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 Mid-level / Intermediate Engineer roles

The three most common job tag items assiciated with mid-level / intermediate Engineer job listings are Engineering, Python 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:

Engineering | 9034 jobs Python | 8765 jobs Machine Learning | 5838 jobs Computer Science | 5632 jobs SQL | 5532 jobs Pipelines | 4924 jobs AWS | 4489 jobs Architecture | 4078 jobs Security | 3700 jobs Testing | 3330 jobs ETL | 3124 jobs Agile | 3124 jobs Azure | 3122 jobs Data pipelines | 3022 jobs Java | 2818 jobs Research | 2732 jobs Spark | 2574 jobs Big Data | 2335 jobs GCP | 2334 jobs APIs | 2159 jobs

Top 20 Job Perks/Benefits for Mid-level / Intermediate Engineer roles

The three most common job benefits and perks assiciated with mid-level / intermediate 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 | 7805 jobs Health care | 4203 jobs Flex hours | 2879 jobs Equity / stock options | 2808 jobs Competitive pay | 2456 jobs Startup environment | 2418 jobs Team events | 1965 jobs Insurance | 1765 jobs Flex vacation | 1749 jobs Salary bonus | 1684 jobs Medical leave | 1651 jobs Parental leave | 1620 jobs Wellness | 1084 jobs 401(k) matching | 959 jobs Relocation support | 552 jobs Conferences | 516 jobs Home office stipend | 514 jobs Unlimited paid time off | 416 jobs Gear | 381 jobs Fitness / gym | 372 jobs

Salary Composition

The salary for a mid-level AI/ML/Data Science engineer typically consists of a base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The composition can vary significantly depending on the region, industry, and company size. In tech hubs like Silicon Valley, the base salary might be higher, but the cost of living is also elevated. In contrast, companies in regions with a lower cost of living might offer a smaller base salary but compensate with generous bonuses or stock options. In larger companies, you might find a more structured bonus system tied to performance metrics, while startups might offer equity as a significant part of the compensation package to attract talent.

Next Steps for Salary Increase

To increase your salary from a mid-level position, consider the following strategies:

• Skill Enhancement: Continuously update your skills with the latest technologies and methodologies in AI/ML. Specializing in a niche area can make you more valuable.
• Advanced Education: Pursuing a master's degree or Ph.D. in a relevant field can open doors to higher-paying roles.
• Leadership Roles: Transitioning into a team lead or managerial position can significantly boost your salary.
• Networking: Building a strong professional network can lead to opportunities in higher-paying companies or roles.
• Certifications: Obtaining advanced certifications can demonstrate your expertise and commitment to the field, potentially leading to salary negotiations.

Educational Requirements

Most mid-level AI/ML/Data Science positions require at least a bachelor's degree in computer science, data science, mathematics, statistics, or a related field. However, many employers prefer candidates with a master's degree due to the advanced knowledge and skills acquired during graduate studies. A strong foundation in mathematics and statistics is crucial, as these are the backbone of machine learning algorithms.

Helpful Certifications

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

• Certified Machine Learning Professional (CMLP)
• TensorFlow Developer Certificate
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate
• Data Science Council of America (DASCA) Certifications

These certifications can validate your skills and knowledge, making you a more attractive candidate to potential employers.

Required Experience

Typically, a mid-level position requires 3-5 years of experience in AI/ML or data science roles. This experience should include hands-on work with machine learning models, data analysis, and familiarity with programming languages such as Python or R. Experience with data visualization tools and cloud platforms can also be beneficial. Employers look for candidates who have successfully completed projects and can demonstrate their ability to apply theoretical knowledge to real-world problems.

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