Top Tech Jobs & Startup Jobs in Chicago, IL

Lead development and deployment of ML and AI solutions for global incentive and quota design. Partner cross-functionally to define quota strategy, build scalable data pipelines and models, create AI agents, evaluate model performance, ensure governance/compliance, and communicate insights to stakeholders to drive business outcomes.

Lead architecture and development of large-scale VM management and monitoring platforms for Azure. Provide technical leadership, design documentation, debugging, performance tuning, operational excellence, mentoring, on-call monitoring, and adoption of AI-assisted workflows to improve reliability, availability, security, and observability across Windows and Linux environments.

Design, develop, and optimize high-performance, low-latency networking infrastructure for large-scale AI training on Azure. Benchmark, debug, and improve scalability, reliability, observability; author design documents; act as DRI and participate in on-call operations.

Design, build, deploy, and operate AI-native systems and LLM-powered applications for Azure capacity orchestration. Lead architecture and design for distributed systems, write and review production-quality code, drive automation and safe deployments, integrate monitoring and on-call reliability practices, and ensure AI safety and security. Collaborate across teams and mentor engineers while shipping scalable, secure solutions.

Lead consultative, value-driven enterprise sales to plan, orchestrate, and deliver AI Workforce solutions (Copilot, Windows 365, Viva, Agents). Build stakeholder strategies, drive pipeline, cross-sell/up-sell, and partner with internal teams to scale AI adoption and measurable business outcomes.

Design, build, and maintain Azure-based full-stack skilling platforms and CI/CD pipelines. Implement scalable microservices, REST APIs, automation, and AI/LLM features, improve site reliability, automate testing, and collaborate across teams to ensure secure, high-quality production deployments.

Design and lead development of Azure platform capabilities and services. Partner with stakeholders to define requirements, produce design documents, mentor engineers, ensure reliability/observability at scale, serve as DRI and on-call, and drive consistency across distributed systems and lifecycle management.

Design, build, benchmark, and operate large-scale reinforcement learning and pretraining systems on NVIDIA and AMD GPU clusters. Optimize distributed, parallel software for training models, gather compute-roadmap data, and collaborate to deliver production-grade conversational and generative AI features.

Lead data science engagements with customers to acquire, clean, analyze, and model data; develop scalable operational models and evaluation methods; coach engineers on best practices; drive solution strategy, ethics, and industry thought leadership; write extensible code and collaborate across teams to deliver cloud-based AI solutions.

Work with customers and cross-functional teams to design, build, and deliver cloud-based solutions. Lead design, identify dependencies, mentor engineers, act as DRI and on-call, and improve availability, reliability, observability, and performance. Contribute to open-source assets and collaborate with Microsoft product teams to produce extensible, maintainable code and scalable solution patterns.