Robotics Engineer Salary in United States during 2024

Salary details

The average Robotics Engineer salary lies between USD 100,000 and USD 181,000 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. 22, 2024

Top 20 Job Tags for Robotics Engineer roles

The three most common job tag items assiciated with Robotics Engineer job listings are Robotics, Engineering and Python. 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:

Robotics | 118 jobs Engineering | 110 jobs Python | 88 jobs Testing | 65 jobs Machine Learning | 57 jobs Computer Vision | 52 jobs Computer Science | 51 jobs Research | 37 jobs Industrial | 36 jobs Linux | 33 jobs CAD | 25 jobs Architecture | 23 jobs Security | 22 jobs PhD | 22 jobs Matlab | 18 jobs SLAM | 16 jobs Agile | 16 jobs Lidar | 16 jobs Git | 15 jobs Prototyping | 14 jobs

Top 20 Job Perks/Benefits for Robotics Engineer roles

The three most common job benefits and perks assiciated with Robotics Engineer job listings are Career development, Health care and Competitive pay. 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 | 76 jobs Health care | 50 jobs Competitive pay | 44 jobs Equity / stock options | 40 jobs Startup environment | 38 jobs Insurance | 31 jobs Flex hours | 29 jobs Flex vacation | 28 jobs Team events | 28 jobs Medical leave | 21 jobs Relocation support | 12 jobs Parental leave | 11 jobs 401(k) matching | 9 jobs Wellness | 9 jobs Fertility benefits | 9 jobs Salary bonus | 7 jobs Unlimited paid time off | 6 jobs Snacks / Drinks | 4 jobs Fitness / gym | 2 jobs Conferences | 2 jobs

Salary Composition

In the United States, the salary composition for AI/ML/Data Science roles can vary significantly based on region, industry, and company size. Typically, the salary is divided into three main components: base salary, bonuses, and additional remuneration such as stock options or equity.

• Base Salary: This is the fixed annual amount and usually constitutes the largest portion of the total compensation. In tech hubs like Silicon Valley, New York, or Seattle, base salaries tend to be higher due to the cost of living and competition for talent.

• Bonuses: These can be performance-based or company-wide and are often a percentage of the base salary. Bonuses are more prevalent in larger companies or those in the finance and tech industries.

• Additional Remuneration: This includes stock options, equity, or other long-term incentives. Startups and tech giants often offer equity as a significant part of the compensation package to attract top talent.

Increasing Salary

To increase your salary from a Robotics Engineer transitioning into AI/ML/Data Science, consider the following steps:

• Specialize in High-Demand Skills: Focus on acquiring expertise in niche areas like deep learning, natural language processing, or computer vision, which are highly valued in the industry.

• Pursue Leadership Roles: Transitioning into managerial or lead roles can significantly boost your salary. This involves developing soft skills such as team management, communication, and strategic planning.

• Network and Build a Personal Brand: Attend industry conferences, contribute to open-source projects, and publish research or articles. Building a strong professional network can open doors to higher-paying opportunities.

Educational Requirements

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

Helpful Certifications

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

• Certified Machine Learning Professional (CMLP)
• TensorFlow Developer Certificate
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate

These certifications can validate your skills and make you more competitive in the job market.

Experience Requirements

Typically, employers look for candidates with 3-5 years of experience in related fields. This experience should include hands-on work with machine learning models, data analysis, and programming languages such as Python or R. Experience in robotics can be a significant advantage, especially if it involves AI applications.

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