Junior Robotics AI Engineer

You will join a tight-knit R&D team crafting next-generation robotic behaviors for diverse sectors—manufacturing, healthcare, logistics, even gaming. From day one you will write production-grade code, tune control algorithms, and see your ideas move real hardware. Expect rapid learning, supportive mentorship, and a clear path toward mid-level leadership.

Key Responsibilities  

- Design, implement, and test robot control algorithms in Python and C++.  

- Integrate perception, navigation, and manipulation modules using ROS 2.  

- Collect and label sensor data (LiDAR, RGB-D, IMU) for machine-learning pipelines.  

- Debug autonomy stacks with Gazebo, RViz, and hardware-in-the-loop simulations.  

- Optimize runtime performance, memory usage, and power draw.  

- Document APIs, architecture decisions, and experiment outcomes.  

- Collaborate with mechanical, electrical, and product teams to ship reliable systems.  

- Contribute to continuous integration and automated test suites.  

What You’ll Bring  

- Bachelor’s degree in Computer Science, Robotics, or a related engineering field.  

- 0-2 years’ hands-on experience in robotics projects (academic or professional).  

- Solid Python skills; familiarity with C++14 or newer.  

- Working knowledge of ROS or ROS 2, URDF, and launch files.  

- Introductory understanding of machine-learning concepts (CNNs, reinforcement learning, SLAM).  

- Comfort with Linux, Git, and shell scripting.  

- Analytical mindset, creative problem solving, and strong written communication.  

- Curiosity to learn—fast.  

Nice-to-Have Extras  

- Coursework or projects in computer vision, control theory, or probabilistic robotics.  

- Exposure to NVIDIA Jetson, Raspberry Pi, or microcontrollers.  

- Experience with cloud robotics, AWS RoboMaker, or edge deployment.  

- Participation in FIRST Robotics, RoboCup, or similar competitions.  

Why You’ll Grow Here  

– Real robots: watch code come alive in physical prototypes.  

– Mentorship: senior AI scientists pair-program and review every pull request.  

– Innovation time: reserve 10% of each sprint for self-directed experimentation.  

– Mission variety: solve challenges across industries, preventing stagnation.  

– Remote culture: distributed team rituals keep communication vibrant, wherever you live.  

Our Culture  

We combine scientific rigor with startup agility. We prize inclusivity, intellectual honesty, and bold experimentation. You will never hear “because we’ve always done it that way.” Instead, you will ask, “what if we tried this?”—and then you will.