Member Of The Technical Staff - Software Engineer (UI/UX)

Transfyr•Cambridge, MA

11d•Onsite

About The Position

Transfyr is building physical AI for science, aiming to create a high-fidelity, machine-readable record of scientific experiments. This infrastructure helps teams learn from failures, transfer knowledge, train scientists, and provide grounded data for models and robots. The company has secured $25M in seed funding and collaborates with leading AI labs and advisors. They are seeking ambitious individuals to tackle complex problems at the intersection of science, perception, machine learning, and robotics.

Requirements

Production front-end engineering experience using TypeScript or JavaScript and a modern component framework like React.
Strong command of UI/UX and interaction design principles, including information architecture, workflow design, visual hierarchy, prototyping, user research, and product judgment.
Experience with complex media and data interfaces, including video, time-series or scientific data, analytics, annotation, browser playback, synchronization, overlays, and rendering performance.
Ability to reason about hybrid application systems, including browsers, APIs, asynchronous processing, cloud services, storage, and edge devices.
Experience with client-side state, caching, long-running workflows, schemas, versioning, validation, and error handling.
Experience with production quality practices such as automated testing, accessibility, observability, performance monitoring, and fault recovery.
Hands-on approach with high agency, capable of taking a problem from user observation through design, production code, and iteration.
User-focused mindset, noticing friction and testing assumptions against actual user workflows.
Systems thinking ability, understanding the impact of data contracts, latency, media behavior, and model uncertainty on the interface.
Reliability, with a focus on testing, observability, maintainability, and supporting shipped products.
Clear and direct communication skills to explain product and architecture decisions across technical and scientific teams.
Intense dedication to the mission and ability to help a small team achieve significant results.

Nice To Haves

Experience with multimodal AI products, scientific software, developer tools, creative tools, or data-labeling platforms.
Experience building semantic search, timeline, transcript, video-review, annotation, or model-adjudication interfaces.
Experience exposing model confidence, evidence, alerts, or failure modes to non-ML users.
Experience creating or extending a design system across multiple product surfaces.
Experience contributing to backend, media-processing, edge, or cloud services that support the product experience.
Experience working directly with scientists, researchers, lab operators, or another expert user group in another domain.
Startup or zero-to-one product experience.
A portfolio demonstrating both engineering depth and thoughtful product craft.

Responsibilities

Design, build, and support interfaces for wet-lab biologists, lab managers, annotators, and customers to use the Transfyr platform.
Make complex data, including synchronized video, audio, transcripts, sensor streams, protocol context, model outputs, annotations, and experimental outcomes, clear and useful for each user.
Take end-to-end ownership of the user experience, from user research and prototyping to production implementation, instrumentation, support, and iteration.
Work closely with backend, perception, and AI/ML engineers on video streaming, overlays, queries, data contracts, and system performance.
Contribute beyond the browser when necessary to deliver a reliable product.
Create reliable interfaces for challenging conditions such as imperfect networks, missing streams, long recordings, changing schemas, browser playback constraints, and evolving model outputs.
Develop a consistent visual and interaction system to make Transfyr’s interfaces clear, fast, and enjoyable.
Build intuitive scientific interfaces that help users understand experimental outcomes, identify deviations, and make decisions.
Create video-data-rich experiences integrating synchronized video, audio, transcripts, sensor data, protocol steps, model outputs, annotations, and experimental results.
Surface the necessary queries, alerts, confidence signals, comparisons, and evidence without obscuring the scientific context.