Computer Vision AI & ML Engineer

Skild AI; San Mateo (CA); Presencial; USD 120.000 - 180.000; Jornada completa

Descripción de la vacante

Skild AI Inc. seeks a Computer Vision AI & ML Engineer to design, build, and deploy perception systems for real-world robotics.

You will work across the full ML lifecycle—from model development and data strategy to evaluation and production integration—driving high-performance vision capabilities in dynamic environments. The role blends applied research with hands-on engineering, influencing architecture and roadmap decisions while collaborating with robotics, simulation, and systems teams to

Formación

• Experience with deep learning models for perception tasks (detection, depth, segmentation).
• Strong Python proficiency and ML lifecycle exposure.
• Familiarity with robotics or real-time systems is a plus.

Responsabilidades

• Develop and optimize deep learning models for depth estimation, 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.

Conocimientos

PyTorch

TensorFlow

Python

3D perception

Uncertainty modeling

Herramientas

Isaac Sim

Gazebo

Blender

Descripción del empleo

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.