deepgram - ML Ops Infrastructure Engineer

• 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, and regression alerts • Develop automated retraining pipelines that trigger on data changes, performance degradation, or scheduled cadences • Create and maintain build and test environments that mirror production, giving researchers high-fidelity feedback before deployment • Establish model versioning, artifact management, and rollback capabilities to ensure safe and reproducible deployments • Collaborate with research engineers to define and enforce model quality gates before production promotion • Build observability dashboards that give the team real-time insight into model health across all environments • Optimize model serving infrastructure for latency, throughput, and cost efficiency • YOU'LL LOVE THIS ROLE IF YOU • Are excited by the challenge of operationalizing cutting-edge AI models at production scale • Believe that great infrastructure is what turns research breakthroughs into customer value • Enjoy designing systems that are automated, reliable, and self-healing • Want to work on problems where minutes of latency reduction or percentage points of accuracy matter enormously • Like collaborating across research and engineering teams to make the whole organization faster • Are motivated by building the deployment and testing systems that back a platform serving over 200,000 developers