Salary for Mid-level / Intermediate Robotics Engineer in United States during 2024

Salary details

The average mid-level / intermediate Robotics Engineer salary lies between USD 90,000 and USD 175,000 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 Mid-level / Intermediate Robotics Engineer roles

The three most common job tag items assiciated with mid-level / intermediate 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 | 29 jobs Engineering | 28 jobs Python | 18 jobs Computer Vision | 13 jobs Computer Science | 12 jobs Machine Learning | 9 jobs Research | 8 jobs Testing | 8 jobs CAD | 7 jobs Mathematics | 7 jobs Industrial | 6 jobs PhD | 6 jobs Physics | 6 jobs Linux | 5 jobs Java | 5 jobs R | 4 jobs Agile | 4 jobs Autonomous Driving | 3 jobs Security | 3 jobs Architecture | 3 jobs

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

The three most common job benefits and perks assiciated with mid-level / intermediate Robotics Engineer job listings are Health care, Career development 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:

Health care | 21 jobs Career development | 19 jobs Equity / stock options | 17 jobs Competitive pay | 17 jobs Insurance | 17 jobs Flex vacation | 14 jobs Flex hours | 13 jobs Startup environment | 11 jobs Team events | 11 jobs Medical leave | 5 jobs Salary bonus | 5 jobs Relocation support | 4 jobs 401(k) matching | 3 jobs Parental leave | 2 jobs Fitness / gym | 2 jobs Unlimited paid time off | 2 jobs Fertility benefits | 2 jobs Wellness | 1 jobs Conferences | 1 jobs Flexible spending account | 1 jobs

Salary Composition

In the United States, the salary composition for a mid-level/intermediate AI/ML/Data Science role can vary significantly based on factors such as region, industry, and company size. Typically, the salary is composed of a fixed base salary, which forms the bulk of the compensation package. This base salary can range from 70% to 85% of the total compensation. Bonuses, which can be performance-based or company-wide, often account for 10% to 20% of the total salary. Additional remuneration may include stock options, especially in tech companies or startups, and other benefits like health insurance, retirement contributions, and paid time off. In regions with a high cost of living, such as the San Francisco Bay Area or New York City, salaries tend to be higher to compensate for living expenses. Similarly, larger companies or those in competitive industries like finance or tech may offer more lucrative packages.

Increasing Salary

To increase your salary further from this position, consider pursuing advanced roles such as Senior Data Scientist, AI/ML Architect, or Technical Lead. These positions often require a deeper specialization in a particular area of AI/ML or data science, as well as leadership skills. Gaining expertise in emerging technologies, such as deep learning, natural language processing, or AI ethics, can make you more valuable. Additionally, taking on more responsibilities, such as leading projects or mentoring junior team members, can demonstrate your readiness for a higher-level role. Networking within the industry and staying updated with the latest trends and technologies can also open up opportunities for advancement.

Educational Requirements

Most mid-level 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 roles that involve complex problem-solving and research. Advanced degrees provide a deeper understanding of machine learning algorithms, data analysis techniques, and statistical modeling, which are crucial for success in this field. Additionally, coursework or experience in software development, data management, and business intelligence can be beneficial.

Helpful Certificates

While not always mandatory, certain certifications can enhance your qualifications and demonstrate your commitment to professional development. Some popular certifications include:

• Certified Data Scientist (CDS): Offered by various organizations, this certification covers essential data science skills and tools.
• TensorFlow Developer Certificate: Demonstrates proficiency in using TensorFlow for machine learning and deep learning projects.
• AWS Certified Machine Learning – Specialty: Validates expertise in building, training, and deploying machine learning models on the AWS platform.
• Microsoft Certified: Azure AI Engineer Associate: Focuses on using Azure services to build AI solutions.

These certifications can help you stand out in a competitive job market and may lead to better job opportunities and higher salaries.

Required Experience

Typically, a mid-level AI/ML/Data Science role requires 3 to 5 years of relevant experience. This experience should include hands-on work with machine learning models, data analysis, and programming languages such as Python or R. Experience with data visualization tools, cloud platforms, and big data technologies is also valuable. Employers often look for candidates who have successfully completed projects that demonstrate their ability to apply AI/ML techniques to solve real-world problems.

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