ML Scientist

Department: ML & Data

Location: San Francisco

Compensation: $185K – $280K • Offers Equity

Employment Type: FullTime

About Wispr

Wispr Flow is making it as effortless to interact with your devices as talking to a close friend.

Today, Wispr Flow is the first voice dictation platform people use more than their keyboards — because it understands you perfectly on the first try. It’s context-aware, personalized, and works anywhere you can type, on desktop or phone.

In 2026, in addition to dictation, we're focused on building native actions — an agentic framework that understands you, and works reliably.

We’re a team of AI researchers, designers, growth experts, and engineers rethinking human-computer interaction from the ground up. We value high-agency teammates who communicate openly, obsess over users, and sweat the details. We thrive on spirited debate, truth-seeking, and real-world impact.

We're grown our revenue +150% every quarter for the last 4 quarters, and have raised $81M from Tier 1 VC firms and other well-known angels.

About the Role

As a ML scientist at Wispr, you’ll play a crucial role in building the first capable, habit forming voice interface that scales to a billion users. Members of our technical staff are responsible for prototyping and designing new features of our voice interface, building infrastructure to handle <500ms LLM inference for millions of requests from everywhere around the world, and scaling the personalization of our speech models and LLMs. You'll be primarily responsible for ML personalization, training speech models, and using fine-tuning and RL techniques to improve LLMs.

What are we looking for?

• PhD in machine learning or related field (neuroscience, EE, etc)

• Strong publication track record at top conferences (ICML, NeurIPS, ICLR, ICASSP)

• Fluency in Python and LLM development

• Attention to detail and eagerness to learn

• Aptitude and clarity of thought

• Creativity in R&D, excellence in engineering, and code velocity

We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.

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