Senior Systems Research Engineer - Embodied AI & Robotics

Intuitive; Sunnyvale (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

Intuitive is seeking a Senior Systems Research Engineer to join a forward-looking robotics team. You will explore and build embodied AI applications at the intersection of AI/ML and robotics, recommending architectures and integrating end-to-end solutions for reliable product development.

You'll collaborate across motion controls, perception, AI/ML, software and hardware teams to transform concepts into robust prototypes while maintaining safety, performance, and quality with a patient-first

Responsibilities

• System architecture and integration of edge AI, firmware, OS, hardware, and cloud services for high reliability.
• Architect data pipelines and real-time systems for sensor fusion, perception, and robotic control with low-latency ML on embedded platforms.
• Apply rigorous software practices, modular architecture, testing, and IP documentation.
• Lead end-to-end embodied intelligence projects; define roadmap for the robotics platform from foundational models to onboard inference.
• Collaborate with motion controls, perception, and hardware teams to address safety requirements.
• Balance technical feasibility with schedules and resources to move from exploration to implementation.

Job description

Job Description

As a Senior Systems Research Engineer, you will join a future-forward team to explore and build embodied AI applications at the intersection of state-of-the-art AI/ML and robotics. In this deeply hands-on technical role, you will recommend performant architectures, and iteratively develop and integrate embodied AI applications to de-risk and demonstrate technical feasibility, performance, and safety. Your goal is to ensure that embodied AI applications are seamlessly developed and integrated into high-quality, reliable product development.

You will act as architect, developer, and integrator, partnering cross-functionally with motion controls, perception, AI/ML, software, and hardware teams to address significant unmet needs. Success in this role requires excelling in an agile, small-team environment—transforming initial concepts into robust prototypes, iterating methodically, and consistently maintaining safety, performance, and quality with a patient-first mindset.

Roles and Responsibilities

• System Architecture & Integration: Design and optimize software interfaces between subsystems, ensuring seamless integration between edge AI, firmware, OS, hardware, and cloud services. You will oversee the deployment and continuous improvement of these systems to ensure high reliability and performance.
• Robotic Control & Data Pipelines: Architect and build robust data pipelines and real-time systems for sensor fusion, perception, and robotic control. You will focus on optimizing AI/ML models specifically for embedded platforms to achieve low-latency execution.
• Engineering Excellence: Apply rigorous software practices, including writing maintainable code, modular architecture, and comprehensive testing. You will document intellectual property and adapt to evolving project needs by exploring diverse frameworks before specializing in high-impact technology stacks.
• Project Ownership & Strategy: Lead complex, end-to-end embodied intelligence projects, making critical architectural decisions and technical trade-offs. You will define the strategic roadmap for the robotics platform—from foundational models to real-time onboard inference—while serving as a core contributor to team planning and design reviews.
• Cross-Functional Collaboration: Partner with motion controls, perception, and hardware teams during early-stage exploration to address clinical, functional, and safety requirements. You will work closely with the research and product development teams to integrate perception, planning, navigation, and multimodal ML models onto edge platforms.
• Iterative Development: Refine designs by balancing technical feasibility with schedules and resource constraints. You will drive the transition from broad technical exploration to deep-dive implementation as the product matures.