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Deepgram

Senior Software Engineer - Applied AI

Deepgram is hiring a Senior Software Engineer - Applied AI in San Francisco, United States. It pays $197k-$307k a year and Level rates it ; you can apply on Deepgram.

Level's read on this job

  • Builds AI ●●●● is how Level rates this software engineer role: the job is building AI systems.
  • Pay on this posting starts 18% higher than the typical software engineer posting on Level.
  • The posting mentions Sierra, Decagon and fine tuning among its tools and skills.
  • Level classes it as a senior role.
  • Deepgram has 67 other open roles on Level.

AI in this role

SierraDecagon
fine-tuningspeech
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 are seeking an engineer to join our Applied AI team dedicated to solving the toughest problems in voice AI for enterprise customers.

We work directly with some of the largest companies deploying voice AI - from leading conversational AI and customer experience platforms to restaurant enterprises and technology partners - taking on the problems that don't have off-the-shelf answers. Much of the work is zero to one.

Current focus areas include:

  • Ultra-robust ASR in noisy outdoor environments

  • Self-service fine-tuning and model adaptation for large enterprise customers

  • High-accuracy, domain-aware voice agents, including drive-thru and phone ordering

  • Robust scoring and evaluation of agents

  • Real-time analytics and operational intelligence

  • Deeper, more reliable on-site hardware integration

We partner with several leading enterprises today and continue to expand these partnerships.

What you'll do

  • Design, develop, and maintain scalable, high-performance backend systems for our platform

  • Improve speech-to-text and text-to-speech quality across an array of environments

  • Expand robust scoring and evaluation of our agents

  • Fine-tune and adapt models for customer-specific vocabulary and domains

  • Optimize the AI pipeline to improve performance in challenging audio environments, robustly handle ambiguous customer requests, and rapidly scale to new domains

  • Run experiments to validate the product impact of new functionality

  • Collaborate closely with the team to ensure seamless integration between our ML models, backend and client devices

It's important to us that you have

  • 4+ years of hands-on experience in developing, implementing, and maintaining cloud infrastructure in production

  • Hands-on applied AI/ML experience that goes beyond using LLMs — training, fine-tuning or adapting models yourself

  • Experience evaluating AI systems, such as building evaluation or scoring for models or agents

  • Excellent problem-solving skills and the ability to adapt to a rapidly evolving startup environment

  • Strong communication skills and the ability to work collaboratively with a team

  • Willingness to problem solve across our entire product

  • Ability to proactively recognize problems and identify solutions to those problems

  • Results oriented and care about the impact of your work

It would be great if you had

  • Experience working with audio

  • Experience with speech-to-text or text-to-speech models

  • Applied research experience, or a background as a research engineer

  • Experience taking a system from zero to one

  • Experience building and maintaining a system that integrates with many 3rd party APIs, particularly Point of Sale systems

  • Experience with Python, Kotlin, or TypeScript

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field

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 careers@deepgram.com.

How we rate this

Senior Software Engineer - Applied AI at Deepgram rates 86 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Fine-tuningSpeechSierraDecagon

Also common in software engineer jobs at this level

Pay

This job starts at
$197k
Typical software engineer job
$167k

This posting starts 18% above the typical software engineer job. See software engineer jobs

Questions you could be asked

  1. Walk me through fine-tuning a model: what data did you use, and how did you check the result?
  2. What have you built with speech recognition or text-to-speech, and where did it break?
  3. What are the limits of Sierra that you've run into, and how did you work around them?
  4. What's a project where you used Decagon hands-on?
  5. How would you decide a model or AI system is ready to ship?

Adapt your resume

  • List these exact terms on your resume: Fine-tuning, Speech, Sierra, and Decagon. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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