Top Tech Jobs & Startup Jobs in Seattle, WA

Design, build, and automate scalable, reliable Commerce platform solutions for Microsoft and Azure. Diagnose and mitigate service issues, use telemetry to improve operations, develop automation and scripts, collaborate cross-functionally, and uphold security and compliance.

Develop data-driven Windows Fundamentals solutions using telemetry and diagnostic signals to improve device reliability, performance, battery life, and sustainability. Responsibilities include defining metrics, analyzing fleet data, building pipelines and dashboards, investigating regressions, implementing operating-system or analytics improvements, validating outcomes, and collaborating with engineering, data science, security, OEM, support, and enterprise teams.

Manages headcount planning, organizational operations, budgeting, forecasting, procurement, vendor management, and employee experience initiatives for the Teamwork Experiences Group. Partners with HR, Finance, Procurement, Chiefs of Staff, and engineering teams to maintain accurate workforce records, optimize budgets, improve workflows, resolve operational issues, and increase sourcing and vendor-management efficiency.

Develop performance tooling for large-scale AI model training and inference. Benchmark, profile, debug, and optimize OpenAI and other LLM workloads across CPUs, GPUs, and Microsoft hardware. Work across compilers, runtimes, libraries, APIs, and other AI software layers to identify regressions, reduce deployment time and hardware requirements, and deliver scalable production improvements. Lead projects and collaborate with researchers, engineers, hardware teams, and external partners.

Recruiter supporting Microsoft’s Global Talent Acquisition team by partnering with business leaders, developing hiring plans, sourcing technical and diverse talent, screening candidates, and improving candidate experience. The role uses market research and recruiting data to guide staffing strategies, ensures compliance throughout the hiring lifecycle, and builds talent pipelines for competitive areas including cybersecurity, AI, and engineering.

Owns a core Microsoft 365 email transport area from strategy and roadmap through delivery and measurable outcomes. Defines product requirements, manages engineering execution, validates secure and compliant mail-flow changes, analyzes telemetry and message data, and improves service metrics. Partners across engineering, Exchange Online, and Microsoft 365 teams while mentoring product managers and leading cross-organizational initiatives.

Leads product marketing strategy for Azure modernization and agentic operations across GitHub Copilot modernization, Azure Migrate, Azure Copilot, and operational services. Oversees a large multidisciplinary team, develops portfolio narratives, drives launches, customer adoption, sales enablement, partner engagement, roadmap alignment, revenue growth, and executive communications. The role requires expertise in AI, application and data modernization, cloud migration, IT operations, and enterprise workloads across Java, .NET, and mainframe environments.

Design and deliver scalable, secure Windows App and Cloud PC client features integrating OS platform capabilities. Lead architecture, reliability, telemetry, incident response, and cross-team collaboration. Mentor engineers and champion AI-assisted development and Responsible AI practices.

Leads a team of applied scientists and engineers developing AI-based speech enhancement, video processing, and ML video codec systems for Microsoft Teams and Windows. Responsibilities include applying AI to real-time media, designing and shipping production platforms, conducting research, securing patents and publications, and managing technical staff. The role requires substantial machine learning research, product development, system architecture, and people management experience.

Research and develop scalable methods for adapting foundation models to enterprise workflows. The role covers post-training, reinforcement learning, fine-tuning, model architecture, inference steering, evaluation, privacy-preserving ML, and multimodal systems. Responsibilities include building production-ready training and inference infrastructure, evaluating models under enterprise constraints, partnering with engineering teams, advancing tool use and agentic behaviors, documenting methods, and mentoring early-career researchers.