Senior Industrial Design​/Computational Designer​/AI Design Engineer - Pico

Overview

Location:

San Jose

Team:

Employment Type:

Regular

Job Code: A224580A

Share this listing:

About Team:
The Innovation Team is part of the Industrial Design organization, with a primary focus on incubating new ideas and product concepts. The team takes a holistic view of the product experience and explores how emerging technologies can be leveraged to create meaningful, delightful, and genuinely useful user experiences. We strongly believe in learning by building. As a result, the team continuously seeks individuals who can rapidly prototype and develop end-to-end product experiences, enabling us to quickly test, validate, and refine ideas through an iterative, fast-paced development cycle.

About the role:

The rapid evolution of technology over the past year has led us to seek a Senior Industrial Designer who is equal parts designer and builder—someone who can move rapidly from concept to functional demos that validate new interaction loops. The person will design physical products as contextual nodes in a distributed system, personally prototyping both hardware and software to validate the critical flow: sensing → inference → feedback → user behavior change.

In the current landscape, it is impossible to validate hardware user experience without functional prototypes. However, as this role sits within the Industrial Design team, the output cannot be limited to rough engineering samples.

The Design Prototype Mandate:
These prototypes serve as iterations—evolving from rough concept validations to more polished versions—and act as the primary tool for the productization phase. The later versions of the prototypes must be professionally designed and robust enough to help the team evaluate critical trade-offs, weigh pros and cons, and make decisions on the final architecture. This blend of aesthetic fidelity and technical functionality is essential for driving true product and experience innovation.

• Architecting the AI Contextual Ecosystem:
  Translate our information architecture into physical form, distributing intelligence across multiple AI devices, wearable hardware, and peripheral nodes.
• Iterative Design Prototyping:
  Lead the build process from initial "works-like" hacking to high-fidelity "Design Prototypes." These artifacts must accurately represent form factor constraints (design intents) to inform engineering and product decisions.
• Sensor Architecture & "Shared Awareness":
  Define the ideal sensor payload to enable AI context perception, ensuring the placement is socially acceptable and functionally optimal. (A big Plus)
• Physical AI Semantics:
  Develop a "physical language" (light, haptics, material form) that makes the AI’s intent legible to the user, ensuring the device feels like a partner rather than a tool.
• Trade-Off Analysis:
  Use these high-fidelity prototypes to demonstrate the benefits and constraints of specific hardware choices to engineering and product teams.

Required Deliverables for Candidates:
We expect this person to deliver high-fidelity concepts, functional prototypes for trade-off analysis, and partnership storyboards that demonstrate the device's role in daily life.

Minimum Qualifications

• Bachelor’s or Master’s in Industrial Design, Computational Design, Mechanical Engineering, Architecture, or a related technical field.
• Hands-on experience with parametric CAD and computational design tools (e.g., Fusion 360, Onshape, Rhino/Grasshopper).
• Strong scripting/programming skills in Python and/or similar languages for CAD automation or geometry processing.
• Familiarity with AI-assisted workflows (simulation, generative form exploration, or design evaluation) and basic cloud-compute environments.
• Comfort working in highly iterative, cross-functional environments with designers, engineers, and prototyping teams.

Preferred Qualifications

• Experience building FeatureScripts in Onshape and/or custom Grasshopper/Python tools in Rhino.
• Experience with cloud-based simulation or optimization (e.g., running design-of-experiments or parameter sweeps at scale).
• Understanding of manufacturing processes and design-for-assembly (DFA) principles, and willingness to partner with…