Senior Systems Research Engineer – Embodied AI & Robotics

Intuitive•Sunnyvale, CA

2d•$167,300 - $283,200•Onsite

About The Position

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.

Requirements

Master’s degree or higher in Computer Science, Computer Engineering, or related technical field; advanced degrees preferred.
Minimum 6 years of embedded systems software development (or equivalent experience), including R&D and innovation environments.
Proficiency in multiple programming languages (e.g., C, C++, Python, Matlab) and building real-time, multi-threaded applications.
Experience with industrial embedded operating systems (e.g., QNX, Yocto), inter-process communication, hardware interfaces, and CUDA programming.
Experience with machine learning models, and frameworks such as PyTorch, TensorFlow, etc
Expertise in developing AI/ML-based embedded solutions, including training and fine-tuning foundation models and hardware acceleration techniques.
Experience in robotics, including motion control, perception, sensor fusion, path planning, and optimizing models for platforms with limited resources.
Strong problem-solving, adaptability to new technologies, and excellent written and verbal communication skills.

Responsibilities

Design and optimize software interfaces between subsystems, ensuring seamless integration between edge AI, firmware, OS, hardware, and cloud services.
Oversee the deployment and continuous improvement of these systems to ensure high reliability and performance.
Architect and build robust data pipelines and real-time systems for sensor fusion, perception, and robotic control.
Optimize AI/ML models specifically for embedded platforms to achieve low-latency execution.
Apply rigorous software practices, including writing maintainable code, modular architecture, and comprehensive testing.
Document intellectual property and adapt to evolving project needs by exploring diverse frameworks before specializing in high-impact technology stacks.
Lead complex, end-to-end embodied intelligence projects, making critical architectural decisions and technical trade-offs.
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.
Partner with motion controls, perception, and hardware teams during early-stage exploration to address clinical, functional, and safety requirements.
Work closely with the research and product development teams to integrate perception, planning, navigation, and multimodal ML models onto edge platforms.
Refine designs by balancing technical feasibility with schedules and resource constraints.
Drive the transition from broad technical exploration to deep-dive implementation as the product matures.