Jobs

Research Engineer, Post-Training

Deepgram

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Location
Remote: United States
Track
AI Researcher
Salary
$150K–$250K / yr
Posted
October 19, 2026
Source
Ashby

Job description

The Opportunity

We'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 Role

You 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 Challenge

We 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 Also 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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