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Wispr AI is building the voice interface for computing. The company's first products—Flow (natural voice interaction in any application) and Notetaker (context-building across conversations)—represent the frontier of human-computer interaction powered by AI.
In this role, you'll drive the creation of new products at the intersection of HCI, AI, and systems design. You'll work closely with the research team to explore emerging interaction patterns, develop hypotheses, build prototypes, and test them with teammates and users. Your responsibilities include:
- Exploring areas such as fast voice actions, computer use, and novel interaction patterns
- Developing hypotheses, prototypes, and experiments for your own ideas
- Building and evolving a harness for in-house models around human-computer interaction
- Improving memory and context retrieval to support different interaction modalities
- Partnering with the ML team to create a bidirectional product–model feedback loop
- Testing, evaluating, and either graduating promising ideas into product areas or documenting why they should be abandoned
- Owning direction and implementation of ideas that prove promising, with increasing scope
You'll operate in an ambiguous, research-forward environment where the ability to form and test hypotheses quickly is critical. Success means building evidence for how Wispr's products should evolve, and ultimately turning validated ideas into real product areas.
The company is talent-dense, holds strong opinions, tests them quickly, and prioritizes both the final human experience and the technology underneath it.
QUALIFICATIONS & REQUIREMENTS:
- Demonstrated ability to take an ambiguous idea from hypothesis to prototype and user or internal testing
- Experience exploring multiple directions and killing ideas when evidence did not support them
- Track record of building something that changed how people interact with a computer, or unusually strong instincts for new interaction patterns
- Close collaboration with researchers or technical collaborators where product needs and model capabilities shaped each other
- Shipped a prototype or product, or can show a rigorous body of experiments and learning even when nothing graduated
- Owned meaningful product direction and implementation when an idea proved promising
- Ability to communicate work clearly through concrete artifacts, technical or product writing, or demos (especially public-facing)
- Deep expertise in HCI, product, and ML is not required; the company prioritizes learning velocity and judgment about what to test, when to stop, and what to pursue
The company sponsors H1B, O1, EB1, L1, STEM OPT, and other visa categories, and will make reasonable efforts to support sponsorship if an offer is extended.
