Engineer Salary in United States during 2024

Salary details

The average Engineer salary lies between USD 122,000 and USD 217,311 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: Nov. 10, 2024

Top 20 Job Tags for Engineer roles

The three most common job tag items assiciated with 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 | 40956 jobs Python | 39919 jobs Machine Learning | 28827 jobs Computer Science | 25710 jobs SQL | 22550 jobs Pipelines | 21337 jobs Architecture | 20853 jobs AWS | 20399 jobs Security | 16426 jobs Testing | 15567 jobs Java | 14004 jobs Agile | 13956 jobs Azure | 13845 jobs Research | 12909 jobs Spark | 12784 jobs Data pipelines | 12592 jobs ETL | 12180 jobs Big Data | 11217 jobs GCP | 11056 jobs APIs | 10147 jobs

Top 20 Job Perks/Benefits for Engineer roles

The three most common job benefits and perks assiciated with Engineer job listings are Career development, Health care and Equity / stock options. 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 | 36842 jobs Health care | 20242 jobs Equity / stock options | 15266 jobs Flex hours | 13466 jobs Startup environment | 11692 jobs Competitive pay | 11639 jobs Team events | 9692 jobs Flex vacation | 9363 jobs Salary bonus | 9126 jobs Insurance | 8851 jobs Medical leave | 8562 jobs Parental leave | 8106 jobs Wellness | 5384 jobs 401(k) matching | 5100 jobs Conferences | 2638 jobs Relocation support | 2567 jobs Home office stipend | 2295 jobs Transparency | 1909 jobs Flexible spending account | 1855 jobs Fitness / gym | 1777 jobs

Salary Composition

In the AI/ML/Data Science field, the salary structure can vary significantly based on region, industry, and company size. Typically, the compensation package is composed of a base salary, performance bonuses, and additional remuneration such as stock options or equity.

• Base Salary: This is the fixed component and usually constitutes the majority of the total compensation. In tech hubs like Silicon Valley, New York, or Seattle, the base salary tends to be higher due to the cost of living and competitive job market.

• Bonuses: Performance bonuses are common and can be tied to individual performance, team success, or company profitability. These bonuses can range from 10% to 20% of the base salary, depending on the company and role.

• Additional Remuneration: Many companies, especially startups and large tech firms, offer stock options or equity as part of the compensation package. This can be a significant portion of the total remuneration, particularly in high-growth companies.

Increasing Salary

To increase your salary from a median of USD 165,000, consider the following strategies:

• Specialize in High-Demand Areas: Focus on niche areas within AI/ML, such as deep learning, natural language processing, or computer vision, which are in high demand and can command higher salaries.

• Pursue Leadership Roles: Transitioning into managerial or lead roles can significantly boost your earning potential. This might involve leading a team of data scientists or managing AI projects.

• Continuous Learning and Certification: Stay updated with the latest technologies and methodologies. Advanced certifications or a master's degree in a specialized area can make you more valuable.

• Networking and Industry Engagement: Attend conferences, workshops, and networking events to connect with industry leaders and explore new opportunities.

Educational Requirements

Most AI/ML/Data Science roles require at least a bachelor's degree in a related field such as computer science, mathematics, statistics, or engineering. However, a master's degree or Ph.D. is often preferred, especially for research-intensive positions. Advanced degrees provide a deeper understanding of complex algorithms and data analysis techniques, which are crucial for high-level roles.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credibility and skill set:

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

These certifications demonstrate proficiency in specific tools and platforms, which can be advantageous in the job market.

Required Experience

Typically, employers look for candidates with 3-5 years of experience in data science or a related field. Experience with data analysis, machine learning models, and programming languages like Python or R is essential. For senior roles, 5-10 years of experience, including project management and team leadership, may be required.

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