Engineering Manager, Active Learning

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 an Engineering Manager to lead the design and implementation of Deepgram’s internal data and ML training systems. You will lead a team of engineers in building crucial components for driving a data flywheel that powers fundamental product quality as well as a system for large-scale, distributed ML training on a HPC cluster. Your ability to partner effectively with leaders and ICs in Research and DataOps while leading talented engineers to build, maintain, and extend mission-critical systems will contribute significantly to Deepgram’s competitive advantage. You will be a critical voice in Deepgram’s DataOps, Research, and Engineering teams, driving high impact products from start to finish. What You’ll Do Recruit, hire, train, and support top engineering talent to build a world-class team Transform cross-functional visions into detailed project plans, ensuring clarity across teams on commitments, risks, and timelines Define and own the technical strategy enabling acceleration of Deepgram’s ML training pipelines Promote a robust team engineering culture, including a focus on rigorous engineering standards as well as continuous improvement on team practices and processes Partner with DataOps and Research to design and implement new services, features, and/or products end to end Coach and mentor engineers to achieve high personal growth while delivering on ambitious team goals 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 See management as an opportunity to empower a team to solve big problems through your own grit, learning, and empathy It’s Important To Us That You Have Proven experience managing and leading and growing a team with a consistent record of mentoring and coaching team members A strong technical background building world class solutions The ability to drive technical decisions in a scalable and thoughtful manner Passion about good engineering practices, emerging technologies, and improving processes A passion for navigating the team through the real-world constraints of a startup: how to build quickly, iterate frequently, and run experiments Strong practical experience with software architecture and implementation, plus the ability to engage with an Engineering team to help build and scale the existing infrastructure It Would Be Great if You Had Experience working in high-growth startups Familiarity with hybrid cloud models (bare-metal datacenters and cloud service providers) and scaled databases Deep experience with machine learning training, inference, or both