ML Engineer - Data

Nuance Labs; Seattle (WA); On-site; USD 90,000 - 120,000; Full time

Job summary

A deep tech startup is seeking individuals to build a groundbreaking human foundation model integrating text, speech, and facial expressions. This role requires experience in scalable data pipelines and the ability to collaborate closely with researchers. Join a team of former top-tier researchers committed to innovation and excellence in AI development.

Qualifications

• At least 1 year of experience in building data pipelines for ML.
• Experience with audio or video data is strongly preferred.
• Ability to turn vague needs into usable tools.

Responsibilities

• Build a unified human foundation model across text, speech, and expressions.
• Understand and generate lifelike, responsive avatars.

Skills

Building scalable data pipelines for ML

Data preprocessing and management

Sourcing and cleaning datasets

Clean coding practices

Collaboration with researchers

Job description

Overview

Nuance Labs is an early-stage deep tech startup. We’re building the first real-time human foundation model — unifying text, speech, and vision — to make AI socially and emotionally intelligent. Imagine an AI that can understand a quirked eyebrow, a shift in tone, or a hesitant pause, and respond in a way that feels truly human.

Key Facts

• $10M seed round backed by Accel, South Park Commons, Lightspeed, and angel investors including the former Chief Product Officer of Synthesia.
• In-person collaboration, 5 days a week, Seattle HQ (with plan to expand to San Francisco).

Role and responsibilities

What you’ll be building is the first human foundation model that operates across text, speech, facial expression, and body language in real time. This unified model:

• Understands fine-grained human signals — from a quirked eyebrow to a subtle change in voice — and infers meaning in context
• Generates lifelike, responsive avatars whose expressions, gestures, and tone evolve frame-by-frame to deliver genuine responses

Required qualifications

• Have at least 1 year of experience building scalable data pipelines for ML, including preprocessing, transformation, and management of datasets. Experience with audio or video data is strongly preferred.
• Are resourceful in sourcing, assembling, and cleaning datasets — with an eye for quality and scale.
• Can partner closely with researchers to turn vague needs (and sometimes half-baked ideas) into robust, usable tools — often anticipating problems and solutions before they’re spelled out.
• Move with urgency and iterate fast.
• Write code that’s clean enough your future self will thank you for.
• Play well with other brilliant minds from different domains.

Why this team

We’re former Apple research scientists who’ve spent years advancing AI avatar and audio-visual generation — publishing at top conferences and shipping ultra-low-latency ML products to millions. We combine frontier research with the ruthless engineering needed for consumer-grade, real-time systems.

• Fangchang Ma: CEO. MIT PhD in Robotics and ML. Previously Research Manager at Apple, with experience at DJI. Published in top AI conferences with 2400+ citations.
• Edward Zhang: CTO. UW PhD in Computer Graphics. Previously Senior research scientist at Apple, with experience at Google, Microsoft.
• Karren Yang: Founding Research Scientist. MIT PhD. Previously senior research scientist at Apple, with experience at Niantic Labs, Meta Reality Labs, Bosch Center for AI, and Adobe Research. Published in top AI conferences with 1800+ citations.

We’re a small, fast-moving research team with an exceedingly high bar — bringing on only the very best talent. Every member has massive ownership, deep trust, and the opportunity to shape both the technology and the company from the ground up.

Culture and values

• Doing right by people — integrity and respect aren’t negotiable.
• Transparency — we communicate openly and share context so everyone can make informed decisions.
• Relentless speed — we bias toward action, iterate fast, and learn quickly.
• In-person collaboration: the best ideas and strongest teams happen face-to-face. Being together fuels our energy, accelerates problem-solving, and sparks creativity.

How to Apply

Email [e-mail] with your CV and a short note on why this role excites you.