Role description
OpenMindAbout OpenMind
OpenMind is building the software that enables intelligent robots to perceive, understand, and operate in the physical world.
We develop and deploy AI-powered robotics solutions across diverse industries and environments. We're looking for a Machine Learning Engineer who can turn real-world challenges into reliable, scalable perception systems deployed on physical robots.
What You will Do
Design and deploy computer vision and ML solutions for robotic inspection, monitoring, anomaly detection, measurement, and scene understanding.
Develop perception pipelines using object detection, classification, segmentation, tracking, video understanding, and multimodal models.
Integrate diverse sensors, including RGB, PTZ, depth and thermal cameras, and LiDAR, with calibration and sensor fusion as needed.
Own projects end-to-end, from system design and model development to optimization, evaluation, deployment, and field debugging.
Build scalable, reusable perception systems and collaborate with robotics engineers and customers to solve evolving real-world challenges.
What we're looking for
Strong foundations in modern computer vision, machine learning, and deep learning, including detection, classification, and semantic segmentation.
Strong engineering fundamentals in languages such as Python, Go, and/or C++, and fluency in PyTorch or JAX.
Solid software engineering and system design skills, with experience building and deploying reliable ML systems.
Demonstrated end-to-end project ownership, with the ability to clearly explain system architecture, technical decisions, trade-offs, and outcomes.
Ability to leverage modern AI tools effectively to accelerate development while maintaining independent technical judgment and a deep understanding of the systems being built.
Strong problem-solving and communication skills, with the ability to work independently and collaborate across technical teams.
Nice to Have
MS or PhD in machine learning, robotics, computer science, or a related field.
Experience with ROS 2 and Docker-based deployment on robots.
Experience deploying and optimizing models on edge hardware (e.g., NVIDIA Jetson) using TensorRT, ONNX, or similar toolchains under latency and memory constraints.
Hands-on experience with LiDAR, 3D perception, sensor calibration, or multi-sensor fusion.
Familiarity with vision-language models, multimodal foundation models, robot control, or active perception.
Work & Benefits
Full-time, on-site, Monday–Friday, 8 working hours per day
Unlimited PTO
Compensation: $130K–$200K
Offers Equity
Opportunity to build and deploy cutting-edge Physical AI solutions on real robots across diverse applications