Top Tech Jobs & Startup Jobs in Chicago, IL

Drive Netflix advertising revenue across Fortune 500 telecommunications clients. Build strategic relationships with CMOs, marketing leaders, agencies, and media directors; sell programmatic and digital video solutions; develop joint business plans and annual agreements; expand client adoption; translate data into measurable strategies; and coordinate with internal teams on brand partnerships, go-to-market plans, and revenue growth. Travel and industry-event representation are required.

Support Netflix live streaming events by improving cloud traffic capacity, scalability, observability, and reliability. Design and execute load, performance, resilience, fault-injection, and functional tests; analyze results; develop capacity plans; debug complex distributed systems; and collaborate across teams during event planning and launches. Participate in on-call rotations and support flexible event-based schedules.

Build foundational advertising account systems for Netflix Ads, including advertiser data models, account hierarchies, enrichment, verification automation, cohort assignment, spend attribution, and customer-facing APIs. The role involves designing scalable, multi-tenant, API-first cloud services with strong governance, reliability, observability, and operational excellence. Engineers will make zero-to-one architectural decisions supporting sales workflows, media planning, programmatic integrations, and advertising growth.

Build and own UI features for Netflix’s TV application across streaming sticks, smart TVs, and cable boxes. Collaborate with product, design, algorithm, and engineering teams to create and refine consumer experiences. Develop TypeScript and JavaScript features using React and Redux, optimize for performance- and memory-constrained devices, conduct A/B testing, and write automated tests using Jest-based frameworks.

Owns product operations for the Content Experience Innovation team, including operating rhythms, OKRs, QBRs, portfolio visibility, roadmaps, tooling, workflows, and leadership communications. Leads cross-functional innovation programs across Product, Engineering, Design, Content, and other teams, improving efficiency through scalable processes, AI, and automation. Partners with senior leadership to shape transformation initiatives and align product development with broader business goals.

Owns end-to-end human evaluation programs for Netflix recommendation quality. Partners with product, ML, data science, UX, engineering, and vendors to design evaluation frameworks, rubrics, metrics, and workflows. Manages annotation capacity, SLAs, costs, rater onboarding, calibration, quality assurance, and delivery timelines. The role also improves operational efficiency, resolves blockers, and translates recommendation strategy into scalable evaluation programs.

Build and maintain data models, pipelines, metrics, dashboards, and analytics supporting Netflix’s advertising identity graph, entity matching, and identity resolution systems. Evaluate match quality, coverage, graph stability, and data drift; collaborate with engineering, data science, product, and identity providers; and communicate technical insights and trade-offs to technical and non-technical stakeholders.

Lead ML initiatives to improve Sales productivity and automation: define roadmap, design and deploy production ML models and AI agents, build measurement pipelines with analytics engineers, iterate from performance and seller feedback, and act as senior technical partner across product, engineering, and Sales to drive measurable revenue impact.

Build AI-augmented gameplay and interactive storytelling systems using generative AI. Integrate LLMs and diffusion models with game engines, behavior trees, narrative systems, and world-building tools. Develop guardrails for safe, balanced, on-theme content; create tools that accelerate prototyping and playtesting; and troubleshoot AI interactions with deterministic game logic. Partner closely with designers to deliver fun, high-quality player experiences with low-latency performance.

Lead research and end-to-end development of machine learning solutions involving LLMs, generative models, summarization, LLM-based evaluation, and recommendation systems. Translate advances in generative AI into business applications, optimize generated content for member impact, partner with engineering and ML teams, define technical roadmaps, and communicate complex concepts to stakeholders.