Robotics AI Engineer
Robotics AI Engineers develop AI systems for robots including perception, planning, manipulation, and human-robot interaction. They work on industrial robots, service robots, and autonomous systems.
What is a Robotics AI Engineer?
Robotics AI Engineers develop AI systems for robots including perception, planning, manipulation, and human-robot interaction. They work on industrial robots, service robots, and autonomous systems.
Education Required
Master's in Robotics, Computer Science, or related field
Certifications
- • ROS Certification
- • Robotics AI Certification
Job Outlook
Growing demand in manufacturing, logistics, and service industries. Combines AI with mechanical systems.
Key Responsibilities
Develop robot perception systems, implement motion planning, build manipulation algorithms, create human-robot interfaces, test robot behavior, and integrate AI with hardware.
A Day in the Life
Required Skills
Here are the key skills you'll need to succeed as a Robotics AI Engineer.
Motion Planning
Planning robot/vehicle movements
Deep Learning
Neural networks and deep learning architectures
Sensor Integration
Integrating sensors with AI systems
Computer Vision
Image and video analysis with ML
Python/C++
Proficiency in Python and C++
ROS
Robot Operating System
Salary Range
Average Annual Salary
$185K
Range: $130K - $240K
Salary by Experience Level
Projected Growth
+35% over the next 10 years
ATS Resume Keywords
Optimize your resume for Applicant Tracking Systems (ATS) with these Robotics AI Engineer-specific keywords.
Must-Have Keywords
EssentialInclude these keywords in your resume - they are expected for Robotics AI Engineer roles.
Strong Keywords
Bonus PointsThese keywords will strengthen your application and help you stand out.
Keywords to Avoid
OverusedThese are overused or vague terms. Replace them with specific achievements and metrics.
💡 Pro Tips for ATS Optimization
- • Use exact keyword matches from job descriptions
- • Include keywords in context, not just lists
- • Quantify achievements (e.g., "Improved X by 30%")
- • Use both acronyms and full terms (e.g., "ML" and "Machine Learning")
How to Become a Robotics AI Engineer
Follow this step-by-step roadmap to launch your career as a Robotics AI Engineer.
Build Robotics Foundation
Learn kinematics, dynamics, control theory, and robotics fundamentals.
Master ROS
Become proficient in ROS/ROS2 for robot software development.
Learn Perception
Study computer vision, SLAM, and sensor fusion for robots.
Study Motion Planning
Understand path planning, manipulation, and motion control.
Practice with Simulation
Use Gazebo, PyBullet, or MuJoCo for robot simulation.
Get Hands-on Experience
Work with physical robots or participate in robotics competitions.
🎉 You're Ready!
With dedication and consistent effort, you'll be prepared to land your first Robotics AI Engineer role.
Portfolio Project Ideas
Build these projects to demonstrate your Robotics AI Engineer skills and stand out to employers.
Build autonomous navigation system with SLAM
Create robot manipulation pipeline with perception
Develop reinforcement learning for robot control
Implement sensor fusion for robust localization
Build simulation environment for robot training
🚀 Portfolio Best Practices
- ✓Host your projects on GitHub with clear README documentation
- ✓Include a live demo or video walkthrough when possible
- ✓Explain the problem you solved and your technical decisions
- ✓Show metrics and results (e.g., "95% accuracy", "50% faster")
Common Mistakes to Avoid
Learn from others' mistakes! Avoid these common pitfalls when pursuing a Robotics AI Engineer career.
Focusing only on simulation without real robot experience
Ignoring hardware limitations in software design
Underestimating sim-to-real transfer challenges
Not considering safety in robot systems
Over-engineering without iterative testing
What to Do Instead
- • Focus on measurable outcomes and quantified results
- • Continuously learn and update your skills
- • Build real projects, not just tutorials
- • Network with professionals in the field
- • Seek feedback and iterate on your work
Career Path & Progression
Typical career progression for a Robotics AI Engineer
Junior Robotics AI Engineer
0-2 yearsLearn fundamentals, work under supervision, build foundational skills
Robotics AI Engineer
3-5 yearsWork independently, handle complex projects, mentor junior team members
Senior Robotics AI Engineer
5-10 yearsLead major initiatives, strategic planning, mentor and develop others
Lead/Principal Robotics AI Engineer
10+ yearsSet direction for teams, influence company strategy, industry thought leader
Ready to start your journey?
Take our free assessment to see if this career is right for you
Learning Resources for Robotics AI Engineer
Curated resources to help you build skills and launch your Robotics AI Engineer career.
Free Learning Resources
- •ROS tutorials
- •MIT Robotics courses
- •Robotics papers
Courses & Certifications
- •Robotics Specialization
- •ROS certification
Tools & Software
- •ROS
- •Gazebo
- •OpenCV
- •Python
- •C++
Communities & Events
- •ROS community
- •Robotics forums
- •Robotics competitions
Job Search Platforms
- •Robotics company careers
- •Research positions
💡 Learning Strategy
Start with free resources to build fundamentals, then invest in paid courses for structured learning. Join communities early to network and get mentorship. Consistent daily practice beats intensive cramming.
Work Environment
Work Style
Personality Traits
Core Values
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