Top Tech Jobs & Startup Jobs in Denver & Boulder, CO

Lead data science strategy across complex customer engagements, turn ambiguous business problems into repeatable ML solutions, define modeling and evaluation standards, drive data readiness and MLOps practices, mentor teams, produce reusable IP, and represent Microsoft in executive and thought-leadership forums.

Design, implement, and optimize large-scale distributed training infrastructure and telemetry for GPU clusters. Profile, benchmark, and debug performance across compute, memory, networking, and storage. Improve collective communication libraries and collaborate with ML researchers and hardware teams to scale models, optimize accelerators, and deliver fleet-wide efficiency improvements and automated recommendations.

Design and develop high-volume, low-latency telemetry and event pipelines for Azure HPC & AI supercomputers. Analyze and improve pipeline fidelity and latency, enable diagnostics for job reliability, partner across teams to deploy end-to-end solutions, lead incident resolution, root-cause analysis, and drive engineering improvements tied to customer outcomes.

Design, implement, test, and maintain cloud-scale services and platform components for security‑critical, highly regulated environments. Collaborate with security, operations, and compliance teams, respond to incidents and on‑call rotations, apply secure‑by‑design principles, and support service reliability and operational excellence.

Design, build, and maintain reliable, high-scale multi-tenant services with emphasis on security, resilience, testability, and automation. Collaborate cross-team, participate in on-call rotation, support live services in Azure air-gapped regions, and contribute to new service buildouts and operational reliability.

Design, implement, and optimize high-performance, low-latency networking solutions for large-scale AI training on Azure. Benchmark, debug, and scale distributed systems, create design documents, write and refactor code, act as DRI including on-call operations, and improve observability, reliability, and performance for AI supercomputing infrastructure.

Build and maintain a capacity management portal and observability features for ML training and inference. Partner with researchers and PMs to turn requirements into intuitive UIs, integrate backend APIs across schedulers and training frameworks, develop internal tooling, and drive architectural improvements and best practices to improve efficiency and model quality visibility.

Lead product marketing for Microsoft AI Content: craft external narratives, define AI quality standards and guardrails, own audience and format strategies globally, partner with Sales to translate capabilities into revenue narratives, and serve as a cross-functional steward aligning Product, Policy, Monetization, and Leadership.

Lead commercial strategy and execution for highly complex Defense Industrial Base accounts. Own multi-year, multi‑affiliate deal constructs, lead executive negotiations, manage financial/contractual/compliance risk, advise on cloud/government approaches, influence cross-functional stakeholders, and ensure forecast accuracy and audit‑ready agreements.

Lead and grow a developer experience team responsible for monorepo strategy, CI/CD, build systems, developer environments, and onboarding. Improve engineering velocity, CI reliability, and developer trust; establish standards, adopt AI-assisted workflows, and partner with infra/ML teams to remove friction for large-scale AI research.