Research Engineer, Post-Training

• At Deepgram, we expect an AI-first mindset—AI use and comfort aren’t optional, they’re core to how we operate, innovate, and measure performance.
• 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.
• 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
• 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
• 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.
• 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

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