About the Team
We are building the future of edge AI — where on-device intelligence meets lightweight, wearable hardware such as Mixed Reality headwear and modular peripherals.
As AI shifts from the cloud to the device, our team is focused on solving the "last inch" of physical interaction: making local AI feel natural, responsive, and seamlessly connected to the user's environment.
You will work alongside mechanical engineers, industrial designers, ML engineers, optical and sensor teams, and human-factors specialists to ship experiences where hardware form, system behavior, and AI capability function as one coherent product.
We are looking for talented individuals to join our team.
As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth.
Successful candidates must be able to commit to an onboarding date by the end of the year.
Please state your availability and graduation date clearly in your resume.
Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply.
The application limit is applicable to our Company and its affiliates' jobs globally.
Applications will be reviewed on a rolling basis - we encourage you to apply early.
Responsibilities
- Partner directly with customers, field teams, engineers, and end users to understand real-world workflows, deployment conditions, and failure points, and translate them into clear UX hypotheses, interaction models, and prototype plans.
- Design forward-deployed UX programs that adapt core product capabilities across industries, environments, and user groups without fragmenting the overall experience.
- Define how on-device AI communicates system state, confidence, progress, uncertainty, limitations, and required user actions across Small Language Models, local multimodal models, vector embeddings, sensor fusion, and hybrid local-cloud architectures.
- Determine which interactions stay local for speed, privacy, reliability, or safety, and which escalate to the cloud, and design graceful degradation under limited connectivity, compute, sensor quality, battery, or model performance.
- Collaborate with ML engineers to understand model behavior and translate technical capabilities into predictable user-facing experiences, balancing inference speed, quality, thermal performance, battery, privacy, and responsiveness.
- Design agentic interaction models — including intent interpretation, task delegation, confirmation, interruption, cancellation, correction, escalation, and recovery — with clear boundaries between autonomous behavior and explicit user control.
- Design understandable representations of agent status (active, waiting, blocked, uncertain, completed, failed, requiring approval) and ensure users can inspect, redirect, pause, or reverse consequential AI actions.
- Work with industrial designers, hardware engineers, optical engineers, sensor teams, and human-factors specialists to translate interaction requirements into physical product implications: sensor placement, button location, display behavior, haptics, weight distribution, visibility, and thermal comfort.
- Design logic-based spatial systems that adapt dynamically to real-time data and hardware form factors, using ambient, haptic, auditory, and visual cues to communicate model state without overwhelming cognitive load.
- Build high-fidelity interactive spatial prototypes and digital simulation frameworks to stress-test multi-agent behaviors against boundary conditions, hallucination spikes, and context-window failures before physical deployment.
- Establish rapid feedback loops between field deployments and central product, design, research, and engineering teams, and identify where issues require software, model, hardware, workflow, or user-education changes