Machine Learning Engineer

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