Backend Engineer- Inference Services

Deepgram
USA | RemotePosted 14 March 2026

Job Description

Backend Engineer- Inference Services 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. Opportunity: Deepgram is looking for a Backend Software Engineer to join the Engine team to lead the design and implementation of Deepgram’s products. You will design and implement secure, robust, and scalable services for speech processing; efficient, distributed compute orchestration; optimized scheduling, and more. Your skill at building highly reusable code that overcomes technical challenges is paired with an intuition for delightful user experiences. You will be a critical voice in Deepgram’s Product and Engineering teams, driving high impact products from start to finish. What You’ll Do - Improve Deepgram’s core inference services including areas in networking, speech processing, audio transcoding, and latency and memory optimization - Develop processes for measuring, building, and optimizing services to maximize system performance - Debug complex system issues that include networking, scheduling, and high performance computing interactions - Rapidly customize backend services to support our customer needs - Partner with Product to design and implement new services, features, and/or products end to end You’ll Love This Role If You - Thrive in a fast-paced, impact-driven environment where learning new skills on-the-fly is not only encouraged but a regular necessity - Enjoy balancing decisions about product and feature maturity to decide when to make minimally invasive changes versus when to incorporate detailed design work It’s Important To Us That You Have - 3+ years of experience in an industry role - Programming experience in Rust (or C, C++), with competence in Python - Excellent communication and organizational skills, both written and verbal. - A high level of experience and understanding of version control; preferably git. - Comprehensive experience with UNIX-style systems. It Would Be Great if You Had - Experience with modern machine learning, such as experience with a framework like Torch or implementation knowledge of architectures like CNNs, RNNS, and transformers - Experience with audio processing BENEFITS & PERKS* HOLISTIC HE ... (truncated, view full listing at source)
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