Description review
Research Engineer, Post-Training
Deepgram · USA - Remote, San Francisco, CA, New York City, NY · back to the listing
HR standards
66/100
needs work
Title ↔ description
68/100
needs work
Reads as
Machine Learning Engineer
98% confident
What this role officially is
data scientist — ESCO, the EU occupation classification
Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.
Also known as: data scientists, data engineer, research data scientist, data expert, data research scientist
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What the listing never says
- 23 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
The listing, marked up
Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.
Company Overview
Deepgram is the leading platform underpinning the emerging trillion-dollar Voice AI economy, providing real-time APIs for speech-to-text (STT), text-to-speech (TTS), and building production-grade voice agents at scale. More than 200,000 developers and 1,300+ organizations build voice offerings that are ‘Powered by Deepgram’, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Daily, Cresta, Granola, and Jack in the Box. Deepgram’s voice-native foundation models are accessed through cloud APIs or as self-hosted and on-premises software, with unmatched accuracy, low latency, and cost efficiency. Backed by a recent Series C led by leading global investors and strategic partners, Deepgram has processed over 50,000 years of audio and transcribed more than 1 trillion words. There is no organization in the world that understands voice better than Deepgram.
Company Operating Rhythm
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.
Every team member who works at Deepgram is expected to actively use and experiment with advanced AI tools, and even build your own into your everyday work. We measure how effectively AI is applied to deliver results, and consistent, creative use of the latest AI capabilities is key to success here. Candidates should be comfortable adopting new models and modes quickly, integrating AI into their workflows, and continuously pushing the boundaries of what these technologies can do.
Additionally, we move at the pace of AI. Change is rapid, and you can expect your day-to-day work to evolve just as quickly. This may not be the right role if you’re not excited to experiment, adapt, think on your feet, and learn constantly, or if you’re seeking something highly prescriptive with a traditional 9-to-5.
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
Notice: We're aware of individuals impersonating Deepgram recruiters. All legitimate Deepgram recruiting communication comes from an @deepgram.com email address. If you've received a message claiming to be Deepgram, please forward it to [email protected].
Deepgram is the leading platform underpinning the emerging trillion-dollar Voice AI economy, providing real-time APIs for speech-to-text (STT), text-to-speech (TTS), and building production-grade voice agents at scale. More than 200,000 developers and 1,300+ organizations build voice offerings that are ‘Powered by Deepgram’, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Daily, Cresta, Granola, and Jack in the Box. Deepgram’s voice-native foundation models are accessed through cloud APIs or as self-hosted and on-premises software, with unmatched accuracy, low latency, and cost efficiency. Backed by a recent Series C led by leading global investors and strategic partners, Deepgram has processed over 50,000 years of audio and transcribed more than 1 trillion words. There is no organization in the world that understands voice better than Deepgram.
Company Operating Rhythm
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.
Every team member who works at Deepgram is expected to actively use and experiment with advanced AI tools, and even build your own into your everyday work. We measure how effectively AI is applied to deliver results, and consistent, creative use of the latest AI capabilities is key to success here. Candidates should be comfortable adopting new models and modes quickly, integrating AI into their workflows, and continuously pushing the boundaries of what these technologies can do.
Additionally, we move at the pace of AI. Change is rapid, and you can expect your day-to-day work to evolve just as quickly. This may not be the right role if you’re not excited to experiment, adapt, think on your feet, and learn constantly, or if you’re seeking something highly prescriptive with a traditional 9-to-5.
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
Notice: We're aware of individuals impersonating Deepgram recruiters. All legitimate Deepgram recruiting communication comes from an @deepgram.com email address. If you've received a message claiming to be Deepgram, please forward it to [email protected].