5 months ago
San Mateo, CA, USAMid Level
H1B sponsor
Responsibilities
- Develop and optimize deep learning models for depth estimation, object detection, segmentation, tracking, and 3D scene understanding using multimodal sensor data.
- Build scalable data processing, training, evaluation, and deployment pipelines for real-world and real-time systems.
- Design labeling strategies and tooling for automated annotation, quality assurance workflows, dataset management, augmentation, and versioning.
- Implement monitoring and reliability frameworks for uncertainty estimation, failure detection, and automated performance reporting.
- Run proof-of-concept experiments and translate research findings into practical perception prototypes.
- Collaborate with robotics, systems, and simulation teams to integrate perception models into production pipelines and improve end-to-end performance.
Requirements
- Strong experience with deep learning frameworks such as PyTorch, TensorFlow, or JAX.
- Background in computer vision tasks including detection, depth estimation, segmentation, tracking, or 3D scene understanding.
- Proficiency in Python; familiarity with C++ is a plus.
- Experience building training pipelines, evaluation frameworks, and machine learning deployment workflows.
- Knowledge of 3D geometry, sensor processing, or multi-sensor fusion involving RGB-D, LiDAR, or stereo.
- Experience with data annotation tools, dataset management, and augmentation techniques.
- Familiarity with robotics, simulation environments such as Isaac Sim, Gazebo, or Blender, or real-time systems.
- Understanding of uncertainty modeling, reliability engineering, or ML monitoring and MLOps practices.
Categories
ML EngineeringRobotics
About Skild AI
Skild AI builds a general-purpose robotic intelligence and software stack to train and deploy robots that adapt to varied, unseen tasks for commercial use. It offers a platform and models for robot manufacturers and enterprises automating physical work, with support for integration across manipulators and mobile systems. Founded in 2023 and headquartered in Pittsburgh, the privately held company raised a Series C in 2026.