Sobre este puesto de Robotics Application Engineer en Skild AI
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're looking for a hands-on, highly technical Robotics Application Engineer to work on the software that bridges our foundation models and real-world deployment. This role sits at the intersection of software development, systems integration, and operations — requiring a blend of technical depth and creative problem-solving. You'll translate complex real-world requirements into robust, deployable robotic solutions and collaborate closely with cross-functional teams to deliver and continuously improve them.
Responsibilities
- Design, develop, and deploy software for robotic systems, including programming, configuration, and validation.
- Integrate and deploy robotic software solutions into production environments.
- Test, troubleshoot, and debug robotic applications — tracing failures across hardware, software, and model layers.
- Work closely with ML and core robotics engineers to surface deployment failures, reproduce edge cases, and translate field learnings into system improvements.
- Analyze and improve robot algorithms and system performance over time.
- Build and maintain technical documentation, runbooks, and tooling to support configuration, monitoring, and performance evaluation.
- Collaborate with hardware, operations, and R&D teams to optimize robotic performance and scalability.
Preferred Qualifications
- BS, MS, or higher degree in Computer Science, Robotics, or a related field, or equivalent practical experience.
- 3–5+ years of hands-on experience in robotics application development, system integration, or field deployment.
- Proficiency in Python and C++; strong working knowledge of ROS/ROS2.
- Familiarity with AI and machine learning techniques as applied to robotic systems.
- Background in autonomous systems — robotics, drones, autonomous vehicles, industrial automation, or similar.
- Familiarity with vision systems, simulation tools, and sensor integration.
- Strong analytical and problem-solving skills with the ability to work in a fast-paced, dynamic environment.