Entry Level Ai Robotics information
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$89.4K is the 25th percentile. Wages below this are outliers.
$87K - $89.9K
26% of jobs
The median wage is $91.5K / yr.
$89.9K - $92.9K
38% of jobs
$92.9K - $95.8K
4% of jobs
$98.2K is the 75th percentile. Wages above this are outliers.
$95.8K - $98.8K
4% of jobs
$98.8K - $101.7K
3% of jobs
$101.7K - $104.7K
4% of jobs
$104.7K - $107.6K
4% of jobs
$107.6K - $110.6K
4% of jobs
$110.6K - $113.5K
4% of jobs
$113.5K - $116.5K
4% of jobs
How much do entry level ai robotics jobs pay per year?
As of Aug 22, 2026, the average yearly pay for entry level ai robotics in the United States is $96,000.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,000.00 and $102,000.00 per year, depending on experience, location, and employer.
Entry level AI robotics jobs are positions designed for individuals who are new to the field of artificial intelligence and robotics, often recent graduates or those transitioning from related areas. These roles typically involve assisting in the design, programming, testing, and maintenance of robotic systems that use AI algorithms. Common job titles include Robotics Engineer (Junior), AI Research Assistant, and Robotics Technician. Responsibilities may include data collection, basic coding, testing prototypes, and supporting senior engineers in developing intelligent robotic solutions.
To thrive as an Entry Level AI Robotics professional, you need a solid grounding in computer science, robotics engineering, and basic programming languages such as Python or C++, usually backed by a relevant bachelor’s degree. Familiarity with robotics platforms (like ROS), machine learning frameworks (such as TensorFlow), and simulation tools is typically expected. Strong problem-solving abilities, teamwork, and effective communication set standout candidates apart. These skills and qualifications are vital for developing, testing, and improving intelligent robotic systems in collaborative and fast-evolving technology environments.
Entry-level AI robotics professionals often encounter challenges such as adapting to complex, multidisciplinary projects that blend software, hardware, and AI algorithms. They may also need to quickly learn new programming languages and frameworks specific to robotics, as well as familiarize themselves with real-time debugging and hardware integration. Effective communication and collaboration with cross-functional teams, including mechanical engineers and data scientists, is essential for success. Additionally, transitioning from academic or theoretical knowledge to practical, real-world applications can require a steep learning curve, but most organizations offer mentorship and structured onboarding to support new team members.
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