Top Tech Jobs & Startup Jobs in Seattle, WA

Manages Central People Operations by overseeing HRIS data accuracy, transactional escalations, workflow automation, SLA performance, reporting, and operational projects. Leads and develops People Solutions Coordinators, establishes procedures and audit frameworks, partners with Payroll, HR, Legal, Risk, and Field Leadership, and uses AI and process improvement to increase efficiency and data quality.

Lead the Applied AI organization, architect AI-focused operating models, manage a team of AI engineers, and redesign business processes for improved efficiency and cost savings.

Own the architecture and technical direction of a high-volume recognition platform spanning edge ingestion, identity resolution, real-time decisioning, notifications, and operator tools. Lead streaming pipeline design, privacy and consent models, observability, reliability, testing, progressive delivery, RFCs, cross-functional alignment, and mentorship. Build systems that combine deterministic rules with probabilistic computer vision signals under physical-world deployment constraints.

Drive corporate financial forecasting, variance analysis, financial modeling, capital allocation, long-range planning, ROI analysis, and OpEx/headcount management. Advise business units, prepare board reporting and dashboards, validate financial data, improve workflows, automate reporting, shorten month-end cycles, and document finance procedures. The role requires strong Excel, ERP/EPM, GAAP, financial analysis, generative AI, data synthesis, executive communication, and multitasking skills.

Lead large cross-functional vision system programs integrating hardware, ML, platform, and product teams. Scope and deliver projects, align internal/external partners, translate customer needs into requirements, troubleshoot field systems, evaluate tradeoffs, mitigate risks, and communicate strategy to technical and non-technical stakeholders to scale vision solutions.

The Senior AI Engineer will design and build AI-powered automation tools, maintain LLM systems, and collaborate with business analysts to enhance processes across various operations.

The Senior Software Engineer will architect and build Metropolis Web Services, focusing on distributed systems and platform infrastructure, optimizing performance, and enabling seamless communication and reliability for various services.

Lead the technical vision of ML Engineering, overseeing data infrastructure, ML pipelines, and team management to transition AI models into production.

As a Senior Machine Learning Engineer, you will design and deploy computer vision models, collaborate with teams, and mentor juniors while ensuring high-performance solutions.

Design, develop, and maintain scalable backend services in Java and Scala; implement gRPC APIs; use Redis, MySQL/PostgreSQL and Kafka for low-latency data and event streaming; deploy and manage microservices on Kubernetes; collaborate with Hardware, ML, and Operations teams; diagnose and resolve performance and scalability issues.