infrastructure
Posted Apr 6ML Ops Infrastructure Engineer
at Deepgram
United StatesRemote
Requirements
- 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.
- 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.
- THE OPPORTUNITY Getting a model from a research notebook to a production API serving millions of requests is one of the hardest problems in AI.
- As an ML Ops Infrastructure Engineer at Deepgram, you will own the critical bridge between research and production -- building the pipelines, deployment systems, and testing infrastructure that take models from experimental to battle-tested at scale.
- Your work ensures that every model improvement our research team makes can be safely, quickly, and reliably delivered to the customers who depend on Deepgram's APIs for real-time voice AI.
- WHAT YOU'LL DO - Design and build CI/CD pipelines specifically tailored for ML model development, validation, and deployment - Architect and maintain model deployment pipelines that move models from research environments through staging to production with confidence - Build A/B testing infrastructure that enables controlled rollouts of new models and measures real-world performance impact - Implement comprehensive monitoring for model performance in production -- accuracy metrics, latency, drift detection,
- experience in MLOps, DevOps, or infrastructure engineering with a focus on ML systems - Strong proficiency in Python and
- experience building automation and tooling for ML workflows - Deep
- experience with CI/CD systems and building pipelines for software and model delivery - Hands-on
- experience with Docker and Kubernetes for containerized workload management - Practical
- experience deploying and serving ML models in production environments - Familiarity with model evaluation, validation, and quality assurance processes - Understanding of monitoring and observability principles as applied to ML systems - Strong problem-solving skills and a bias toward automation over manual processes IT WOULD BE GREAT IF YOU HAD -
- Experience with model serving frameworks such as NVIDIA Triton Inference Server, TensorRT, or ONNX Runtime - Background in speech, audio, or real-time media ML systems -
- Experience with Infrastructure as Code tools such as Terraform or Pulumi - Hands-on
- experience with monitoring and observability stacks (Prometheus, Grafana, Datadog, or similar) - Familiarity with GPU-accelerated inference optimization and profiling -
- Experience with feature stores, data versioning, or ML metadata management - Knowledge of canary deployment strategies and progressive delivery for ML models BENEFITS & PERKS
- If you're looking to work on cutting-edge technology and make a significant impact in the AI industry, we'd love to hear from you! Deepgram is an equal opportunity employer.
Benefits
- HOLISTIC HEALTH - Medical, dental, vision
- benefits - Annual wellness stipend - Mental health support - Life, STD, LTD Income Insurance Plans WORK/LIFE BLEND - Unlimited PTO - Parental leave - Flexible schedule - 12 Paid US company holidays - Quarterly personal productivity stipend - One-time stipend for home office upgrades - 401(k) plan with company match - Tax Savings Programs CONTINUOUS LEARNING - Learning / Education stipend - Participation in talks and conferences - Employee Resource Groups - AI enablement workshops / sessions *For candidates
- Backed by prominent investors including Y Combinator, Madrona, Tiger Global, Wing VC and NVIDIA, Deepgram has raised over $215M in total funding.
Additional details
- 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.
- 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.
- benefits are administered locally and governed by country-specific regulations. Because of this,
- benefits will differ by region — in some cases international employees receive
- benefits US employees do not, and vice versa. As we scale, we will continue to evaluate where we can create more alignment, but a 1:1 global
- benefits structure is not always legally or operationally possible.