Top AI & Machine Learning Jobs in Chicago, IL

Own the end-to-end product experience for AI coding agents integrating Deepgram: discovery, integration/onboarding, production use, verification, and feedback systems. Build measurement, experimentation, and optimization systems; define agent-specific developer platform requirements and prototype changes; turn agent traffic into rapid product improvements and run cross-functional execution.

As a Data Scientist at Deepgram, you'll tackle complex audio data challenges, develop scalable data pipelines, and collaborate with teams to advance voice AI technologies.

Design and build scalable, automated evaluation pipelines and infrastructure to validate speech, audio, and multimodal models. Translate research benchmarks into enforceable pass/fail gates, run batch and streaming tests, operate canaries and continuous monitoring, integrate quality gates into CI/CD, and partner with research, training, inference, and infra teams to prevent regressions and ensure production model quality.

Lead end-to-end design and execution of voice data programs: build ingestion pipelines, labeling specs, tooling, and quality safeguards; align data strategy with research and product; manage vendors and teams; track throughput, quality, and vendor performance; and prototype/deploy data tools to scale datasets that improve speech and voice AI model outcomes.

Own and grow the self-serve developer funnel from first touch to paid customer. Define and ship product changes across onboarding, console, and activation. Build instrumentation, experimentation, and business rhythms; run rapid hypotheses, measure outcomes, and collaborate with engineering, design, dev rel, marketing, sales, and analytics.

Own technical and strategic partner relationships for infrastructure platforms (silicon, cloud, edge, confidential computing). Lead onboarding, POCs, demos, deployment guidance, troubleshooting, and joint go-to-market to drive adoption and expansion of Deepgram’s voice AI on partner hardware and platforms.

Lead and build Deepgram's AI enablement function: prototype and ship reusable agents, MCP servers, paved-road workflows, prompt and retrieval patterns, and an enablement hub. Drive company-wide AI adoption with measurable productivity metrics, embed safe-use guardrails, partner across Platform, Security, Data, and People Ops, and grow a central team and distributed champions network.

Lead end-to-end delivery of ML infrastructure and AI tooling programs, defining architecture and rollout strategies for training, serving, and monitoring. Coordinate research, engineering, product, and data teams to optimize inference cost/latency, build internal tools for experiment tracking and model versioning, and resolve bottlenecks to enable faster, scalable ML deployments.

Design and implement scalable, secure inference services for speech processing. Optimize networking, audio transcoding, latency, memory, and distributed compute orchestration. Debug complex system issues, customize backend services for customers, and partner with Product to deliver end-to-end features.

Own the research-to-production pipeline: harden training/evaluation workflows, build packaging/deployment tooling, design release gates, optimize inference and serving for latency/throughput, establish benchmarking and validation, and instrument feedback from production to accelerate research iteration.