Top Tech Jobs & Startup Jobs in Seattle, WA

Conduct security research focused on next-generation intrusion and anomaly detection. Analyze large-scale security event data, develop machine learning and statistical models, and design scalable, low-latency analytics platforms using streaming, graph-based, and representation-learning techniques. Collaborate with researchers, product teams, and engineers to transition concepts into deployed systems, while publishing and presenting findings in leading security, systems, and data-management venues.

Lead a team building automated systems and tools to discover, explain, and remediate vulnerabilities in native Windows code. Develop scalable detection methods, enable automated security testing for developers, collaborate with product teams, and drive team clarity and execution.

Develop machine learning techniques focused on AI safety, alignment, and trustworthiness. Collaborate with product, research, and engineering teams to design, build, deploy, monitor, and iterate responsible AI systems at scale, from experimentation to production for large language models and distributed AI services.

Leads pre-silicon verification for complex chip IP, subsystems, and blocks. Develops UVM-based environments, test plans, simulations, random stimulus, coverage strategies, checkers, and debugging workflows. Drives verification closure across product cycles, improves methodologies and tools, applies generative AI, and mentors engineers. The role requires collaboration with design teams and expertise in protocols such as CHI, AMBA, AXI, PCIe, and CXL.

Supports security assurance for Microsoft government cloud services by analyzing threats, vulnerabilities, and operational security issues. Helps develop mitigation strategies, conduct security reviews, coordinate incident responses, produce analysis reports, and communicate findings to decision-makers. Contributes to threat modeling, secure software development guidance, security research, and assurance planning while collaborating with security teams, customers, and partners.

Partners with engineering leaders on resource allocation, investment optimization, workforce planning, financial analysis, forecasting, and portfolio health. Builds models and business insights, monitors performance against plan, identifies risks and tradeoffs, and improves financial processes. Serves as a trusted advisor to leadership, influencing expense management and investment decisions through data-driven analysis and effective storytelling.

Develop scalable AI-powered operations and ML infrastructure for reliable, secure cloud systems. Design distributed systems, write maintainable code, improve architecture and operational excellence, mentor engineers, establish engineering standards, and lead testing, incident response, and on-call activities. The role requires Azure or cloud experience, coding proficiency, and expertise in automation, reliability, CI/CD, infrastructure as code, and responsible AI practices.

Leads a software engineering team responsible for Microsoft Purview platform services, including authorization, policies, alerts, audits, and scopes. Owns feature delivery from strategy through customer adoption; drives architecture, reliability, security, compliance, operational excellence, and modernization. Coaches engineers, manages performance and career development, coordinates cross-functional roadmaps, oversees incident readiness and technical debt, and communicates risks and progress to senior leadership.

Designs algorithms and applications for fault-tolerant quantum computers. Develops modeling tools to assess quantum resource requirements across hardware architectures and creates application- and architecture-aware techniques for quantum circuit compilation and optimization. The role involves research and software development, cross-functional collaboration, and advancing quantum applications, platforms, and hybrid quantum-classical workflows.

Build and optimize distributed systems supporting large-scale reinforcement learning, LLM post-training, inference, and production AI workloads. Develop reliable platform services, improve researcher iteration loops, debug model-hardware interactions, optimize performance, and enhance observability, security, scalability, and operational reliability. Participate in architecture, coding, incident response, deployment planning, and on-call support. Required qualifications include a technical bachelor’s degree or equivalent experience and at least two years of software engineering experience.