Member of Technical Staff - Agents

Requirements

• Experience as an early-stage founder or engineer at an agent-focused startup.
• Deep engagement with contemporary agent research, frameworks, and tooling.
• Proven experience taking experimental or research-driven systems into production environments.

Additional Information

About Dimensional Dimensional is building the foundation for physical intelligence in general-purpose robotics. We develop a unified framework that enables robots to perceive, reason, learn, and act across diverse real-world environments and embodiments. Dimensional's mission is to make physical intelligence programmable, scalable, and accessible -- accelerating the development of generalist robots that can adapt, learn, and perform reliably in the real world. Our platform sits between robot hardware and AI models, providing a modular, composable architecture for training and deploying robotic intelligence at scale. By abstracting hardware differences and standardizing core capabilities-such as perception, spatial understanding, decision-making, and control-Dimensional allows developers and partners to build, transfer, and operate robotic skills efficiently across platforms. About This Role We're hiring an LLM Engineer to build intelligent agent systems that interact with robotic platforms. This role blends cutting-edge agent development with real production constraints - you'll be expected to ship, not just prototype. You might be an ex-founder or early engineer from an agent-focused startup, or someone deeply embedded in the modern agent ecosystem who can still operate within a rigorous production codebase. Core Responsibilities Build, deploy, and operate single-agent and multi-agent systems. Design and develop multimodal agent architectures. Integrate agent systems into production robotics workflows. Contribute high-quality pull requests to a shared, large-scale codebase. Optimize inference performance, deployment pipelines, and overall system reliability. What We Look For Hands-on experience designing, building, and deploying agent systems. Strong software engineering fundamentals, with the ability to deliver production-quality code. Comfort working within complex, shared codebases and collaborating across teams. Familiarity with modern agent frameworks, tooling, and development workflows. High technical bar, with strong judgment around code quality, system design, and reliability.

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Company Intel

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