About 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