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Skild AI
Posted 124 days agoVerified live 1d ago

Computer Vision AI & ML Engineer

Brief overview

San Mateo, California, United StatesIn-person
15 H-1B approvalsDept. of Labor
Deep learningComputer visionModel developmentData pipeline constructionML deployment3D scene understandingSensor fusionPythonC++MLOpsUncertainty estimationFailure detectionReal-time systemsDataset managementData augmentationSimulation environmentsRobotics integration

About the company

Skild AI logo
Skild AIskild.ai

Robotics and AI research company.

Visa sponsorship history

3 years sponsoring, last filed FY2026

Data powered by U.S. Department of Labor. This does not guarantee sponsorship for this specific role.
15H-1B approved
100%approval rate
12new H-1B hires
$250,000median wage / yr
H-1B Petition ApprovalsVisas USCIS actually granted: the strongest sign the company sponsors.
20241
20257
20267
LCA Certified ApplicationsAn early filing step, not a visa approval: it signals intent, not confirmed sponsorship.
20241
20262
Top sponsored roles
Research EngineerMachine Learning EngineerMachine Learning Engineer, Reinforcement Learning

Job description

Company Overview

At Skild AI, we are building the world's first general purpose robotic intelligence that is robust and adapts to unseen scenarios without failing. We believe massive scale through data-driven machine learning is the key to unlocking these capabilities for the widespread deployment of robots within society. Our team consists of individuals with varying levels of experience and backgrounds, from new graduates to domain experts. Relevant industry experience is important, but ultimately less so than your demonstrated abilities and attitude. We are looking for passionate individuals who are eager to explore uncharted waters and contribute to our innovative projects.

Position Overview

We are seeking a Computer Vision AI & ML Engineer to design, build, and deploy advanced perception systems for real-world robotics and automation. You will work across the full machine learning lifecycle—model development, data strategy, evaluation, and production integration—to deliver robust, high-performance vision capabilities. This role combines applied research with hands-on engineering and offers the opportunity to influence both architecture and roadmap decisions.

Responsibilities

  • Develop and optimize deep learning models for depth estimation, object detection, segmentation, tracking, and 3D scene understanding using multi-modal sensor data.
  • Build scalable pipelines for data processing, training, evaluation, and deployment into real-world and real-time systems.
  • Design labeling strategies and tooling for automated annotation, QA workflows, dataset management, augmentation, and versioning.
  • Implement monitoring and reliability frameworks, including uncertainty estimation, failure detection, and automated performance reporting.
  • Conduct proof-of-concept experiments to evaluate new algorithms and perception techniques; translate research insights into practical prototypes.
  • Collaborate with robotics, systems, and simulation teams to integrate perception models into production pipelines and improve end-to-end performance.

Preferred Qualifications

  • Strong experience with deep learning frameworks (PyTorch, TensorFlow, or JAX).
  • Background in computer vision tasks such as 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 ML deployment workflows.
  • Knowledge of 3D geometry, sensor processing, or multi-sensor fusion (RGB-D, LiDAR, stereo).
  • Experience with data annotation tools, dataset management, and augmentation techniques.
  • Familiarity with robotics, simulation environments (Isaac Sim, Gazebo, Blender), or real-time systems.
  • Understanding of uncertainty modeling, reliability engineering, or ML monitoring/MLOps practices.

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