Software Engineer - Applied AI (Senior or Staff Level)

FDE Times; San Francisco (CA); Presencial; USD 180.000 - 240.000; Jornada completa

Descripción de la vacante

Deepgram is seeking an engineer to join our Applied AI team focused on solving tough voice AI problems for enterprise customers. You will design scalable backend systems, improve STT/TTS quality, and iterate on model adaptation for enterprise domains.

We value hands-on AI/ML work, experience evaluating AI systems, and strong collaboration across teams. The role involves rapid experimentation and integration with ML models, backend platforms, and client devices.

Formación

• 4+ years of hands-on experience building and maintaining production cloud infrastructure.
• Hands-on AI/ML experience beyond using LLMs—training, fine-tuning, or adapting models.
• Experience evaluating AI systems with metrics, scoring, or evaluation tooling.
• Strong problem-solving skills and ability to adapt in a fast-paced startup.
• Excellent communication and cross-team collaboration capabilities.

Responsabilidades

• Design, develop, and maintain scalable, high-performance backend systems for the platform.
• Improve speech-to-text and text-to-speech quality across environments.
• Expand robust scoring and evaluation of agents.
• Fine-tune and adapt models for customer vocabularies and domains.
• Optimize AI pipeline for performance in challenging audio environments and scale to new domains.
• Run experiments to validate product impact of new functionality.
• Collaborate with ML, backend, and client-device teams for seamless integration.

Conocimientos

Cloud infra expertise

Applied AI/ML

Model evaluation

Problem solving

Collaboration

Educación

Bachelor's or Master's in CS/Engineering

Herramientas

Python

Kotlin

TypeScript

Descripción del empleo

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