Top Tech Jobs & Startup Jobs in Seattle, WA

Leads project management across AI and Developer Platforms, establishing scalable operating models, planning frameworks, governance, risk management, and delivery standards. Manages and develops a distributed Project Management team, oversees portfolio and execution rhythms, aligns cross-functional stakeholders, resolves trade-offs, and provides leadership visibility into progress, dependencies, risks, resources, and outcomes. Uses data, automation, dashboards, and AI to improve delivery efficiency and organizational decision-making.

Build and operate secure, scalable AI compute platform services, including backend APIs, asynchronous workflows, Kubernetes controllers, and multi-tenant workload capabilities. The role focuses on distributed training and inference, platform reliability, observability, developer tooling, and infrastructure simplification. Responsibilities include collaborating across engineering teams, improving scalability and developer productivity, and providing technical leadership for production AI platform capabilities.

Design and build secure, scalable platform services for distributed AI training and inference. Develop backend APIs, Kubernetes controllers, orchestration systems, asynchronous workflows, multi-tenant access controls, and developer tools. Improve reliability, observability, scalability, and engineering productivity while partnering with infrastructure and AI teams. The role also provides technical leadership, mentoring, and cross-functional collaboration throughout platform development and production delivery.

Design and lead development of robotics software foundations connecting sensing, planning, control, actuation, middleware, operating systems, and hardware accelerators. Build APIs, SDKs, diagnostics, testing workflows, and production-ready reference platforms for Arm-powered devices. Optimize real-time performance, reliability, safety, and resource usage while mentoring engineers and collaborating across robotics, AI, hardware, product, and customer teams.

Designs and develops highly available cloud services for AI inference workloads. Responsibilities include building Kubernetes controllers and platform capabilities for deployment, scheduling, scaling, recovery, upgrades, observability, and lifecycle management. The role leads production readiness reviews, resolves complex infrastructure issues, improves reliability and performance, drives architecture and design reviews, mentors engineers, and influences technical direction across teams.

Lead research and development of perception algorithms for Physical AI, including detection, segmentation, tracking, localization, sensor fusion, and scene understanding. Define rigorous datasets, experiments, metrics, and evaluation pipelines, then optimize models for real-time deployment across Arm CPUs and AI accelerators. Collaborate with robotics, controls, hardware, product, and customer teams; mentor technical staff; guide on-device perception roadmaps; and contribute through publications, patents, and open-source work.

Lead the architecture and hands-on development of distributed AI inference runtime systems. Responsibilities include scheduling, batching, KV-cache and memory management, distributed execution, kernel optimization, profiling, benchmarking, and performance analysis. Enable new model architectures, improve latency and throughput, develop validation and safe-rollout systems, and collaborate with infrastructure, compiler, hardware, cloud, and research teams. Mentor engineers and establish performance-engineering practices for Arm’s production AI platform.

Designs, builds, and operates large-scale AI compute infrastructure for training, fine-tuning, evaluation, and inference. Responsibilities include managing Kubernetes clusters, enabling CPU and GPU systems, optimizing scheduling and capacity, troubleshooting distributed infrastructure, and automating provisioning, upgrades, monitoring, and maintenance. The role partners closely with AI researchers and engineers to improve infrastructure reliability, scalability, performance, and developer productivity.

Lead the architecture and development of highly available cloud services for AI inference. Build Kubernetes controllers and platform capabilities for workload scheduling, scaling, recovery, deployment, and lifecycle management. Improve reliability, observability, performance, and resource efficiency through production readiness reviews and incident-driven improvements. Guide complex technical initiatives, mentor engineers, resolve infrastructure issues, and align architecture across AI compute, runtime, and product teams.

Develop control algorithms and production embedded software for robotic and autonomous systems on Arm platforms. Design dynamic models, estimators, controllers, and real-time architectures; validate performance through simulation, software-in-the-loop, hardware-in-the-loop, and physical testing. Provide technical leadership across control theory, robotics, sensing, actuation, and embedded implementation. Mentor engineers, lead technical reviews, optimize execution for constrained hardware, and collaborate across robotics, perception, hardware, safety, and product teams.