The OpportunityWe're building the engine that solves customer challenges at scale. When customers hit a limit in our voice AI, you'll measure it, fix it, and ship the fix to every customer in weeks.
Example projects:
- Expanding our models to new languages and regions
- Improving how text-to-speech pronounces names, terms, and numbers
- Isolating a speaker's voice from background noise and crosstalk
- Giving customers early access to new voice capabilities, like steerable and cloned voices, and using their feedback to guide the research methodology
- Releasing new benchmarks for Voice AI use-cases
The RoleYou will thrive in this role if you enjoy:
- Turning vague customer problems into clear metrics
- Using whatever works to fix them, including fine-tuning, new data, and external models
- Shipping work that customers use within weeks
The ChallengeWe are seeking researchers who:
- Own a customer problem until it measurably improves in production
- Find the fastest path to a fix, even if it's an approach no one has tried
- Can tell when a result is ready for customers
If these expectations energize you, you might be the person we need. This role takes focus on the customer's problem, creativity in approach, and a strong drive to ship.
What You'll Do - Find where our models fall short and set targets for improvement
- Design evaluations that show whether a model is better and why
- Curate and generate data and fine-tune models
- Build working systems quickly and ship them to production
We don't require a specific degree. Show us hard problems you've solved in past projects, shipped systems, or open source work.
You May Be a Good Fit If You Have- Deep experience training, fine-tuning, and evaluating deep learning models
- Strong Python and PyTorch skills
- A track record of shipping ML to production
- A habit of owning problems end to end and learning what you need along the way
- Good judgment about which problems matter and when a result is ready to ship
Strong Candidates May Have- Experience with speech-to-text, text-to-speech, or voice agents
- Experience with distributed training
- Published papers, open source contributions, or public benchmarks
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