Job Summary:
Skild AI is building the world's first general purpose robotic intelligence that adapts to unseen scenarios. They are seeking a Computer Vision AI & ML Engineer to design, build, and deploy advanced perception systems for robotics and automation, working across the full machine learning lifecycle.
Responsibilities:
โข Develop and optimize deep learning models for depth estimation, object detection, segmentation, tracking, and 3D scene understanding using multi-modal sensor data.
โข Build scalable pipelines for data processing, training, evaluation, and deployment into real-world and real-time systems.
โข Design labeling strategies and tooling for automated annotation, QA workflows, dataset management, augmentation, and versioning.
โข Implement monitoring and reliability frameworks, including uncertainty estimation, failure detection, and automated performance reporting.
โข Conduct proof-of-concept experiments to evaluate new algorithms and perception techniques; translate research insights into practical prototypes.
โข Collaborate with robotics, systems, and simulation teams to integrate perception models into production pipelines and improve end-to-end performance.
Preferred:
โข Strong experience with deep learning frameworks (PyTorch, TensorFlow, or JAX).
โข Background in computer vision tasks such as detection, depth estimation, segmentation, tracking, or 3D scene understanding.
โข Proficiency in Python; familiarity with C++ is a plus.
โข Experience building training pipelines, evaluation frameworks, and ML deployment workflows.
โข Knowledge of 3D geometry, sensor processing, or multi-sensor fusion (RGB-D, LiDAR, stereo).
โข Experience with data annotation tools, dataset management, and augmentation techniques.
โข Familiarity with robotics, simulation environments (Isaac Sim, Gazebo, Blender), or real-time systems.
โข Understanding of uncertainty modeling, reliability engineering, or ML monitoring/MLOps practices.
Company:
Skild AI develops artificial intelligence systems that enable robots to act in physical environments. Founded in 2023, the company is headquartered in Pittsburgh, USA, with a team of 11-50 employees. The company is currently Early Stage.