Engineer Salary in United States during 2024

Salary details

The average Engineer salary lies between USD 120,500 and USD 215,000 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: Dec. 15, 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 | 48514 jobs Python | 47192 jobs Machine Learning | 34625 jobs Computer Science | 30261 jobs SQL | 26500 jobs Pipelines | 25263 jobs Architecture | 24794 jobs AWS | 24006 jobs Security | 19638 jobs Testing | 18385 jobs Azure | 16543 jobs Java | 16427 jobs Agile | 16409 jobs Research | 15344 jobs Data pipelines | 14836 jobs Spark | 14727 jobs ETL | 14279 jobs Big Data | 13046 jobs GCP | 13009 jobs APIs | 12060 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 | 43684 jobs Health care | 23357 jobs Equity / stock options | 17616 jobs Flex hours | 15614 jobs Startup environment | 13615 jobs Competitive pay | 13506 jobs Team events | 11352 jobs Flex vacation | 10738 jobs Salary bonus | 10498 jobs Insurance | 10152 jobs Medical leave | 9817 jobs Parental leave | 9240 jobs Wellness | 6234 jobs 401(k) matching | 5741 jobs Conferences | 3061 jobs Relocation support | 3038 jobs Home office stipend | 2547 jobs Transparency | 2261 jobs Fitness / gym | 2057 jobs Flexible spending account | 2039 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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