Software Engineer - Applied AI (Senior or Staff Level)

Reposted One Month Ago
2 Locations
In-Office
197K-307K Annually
Mid level
Artificial Intelligence • Machine Learning • Natural Language Processing • Software • Conversational AI
Deepgram builds research-driven Voice AI to power the human-to-machine interactions of the future.
The Role
As a Software Engineer at Deepgram for Restaurants, you'll design and maintain scalable backend systems for automated ordering, integrating AI models, optimizing performance, and ensuring smooth interactions with restaurant software.
Summary Generated by Built In
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 [email protected].

Skills Required

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field
  • 4+ years of hands-on experience in developing, implementing, and maintaining backend infrastructure in production environments
  • Proven track record of building and deploying scalable, high-performance backend systems
  • Experience with cloud-based infrastructure and deployment technologies, such as AWS and API design
  • 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

What the Team is Saying

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Deepgram Compensation & Benefits Highlights

  • Healthcare Strength — Offerings include medical, dental, vision, mental-health support, wellness stipends, and life/short- and long-term disability insurance; feedback suggests this breadth is a notable strength for U.S. employees.
  • Parental & Family Support — Multiple sources report 16 weeks of fully paid parental leave; feedback suggests family leave is a standout element of the package.
  • Leave & Time Off Breadth — Unlimited PTO, 12 paid U.S. holidays, and flexible schedules are consistently listed; feedback suggests time off policies emphasize flexibility and work-life balance.

Deepgram Insights

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The Company
HQ: San Francisco, CA
150 Employees
Year Founded: 2015

What We Do

Deepgram is the leading voice AI platform for developers building speech-to-text (STT), text-to-speech (TTS) and full speech-to-speech (STS) offerings. 200,000+ developers build with Deepgram’s voice-native foundational models – accessed through APIs or as self-managed software – due to our unmatched accuracy, latency and pricing. Customers include software companies building voice products, co-sell partners working with large enterprises, and enterprises solving internal voice AI use cases. The company ended 2024 cash-flow positive with 400+ enterprise customers, 3.3x annual usage growth across the past 4 years, over 50,000 years of audio processed and over 1 trillion words transcribed. There is no organization in the world that understands voice better than Deepgram.

Why Work With Us

Our culture, like our product, is constantly learning and evolving, but the heart of our team is enduring. We are a self-motivated, positive, passionate, and competitive group of people. At Deepgram, we put an emphasis on being ourselves, being curious, growing together, and being human. We are a unique bunch who celebrate our differences.

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Deepgram Offices

Remote Workspace

Employees work remotely.

Typical time on-site: None
HQSan Francisco, CA
Ann Arbor, MI
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