Top Tech Jobs & Startup Jobs in Seattle, WA

Optimize and compress large language and vision models for on-device inference. Build model distillation and hardware-specific compilation pipelines, and benchmark performance across various NPU/GPU architectures to enable efficient edge deployment.

Design and architect multi-agent orchestration frameworks, build robust tool-calling pipelines and reasoning loops, and optimize latency and token usage for real-time agentic workflows. Apply expertise in multi-agent frameworks and agentic RAG to enable autonomous tool invocation and scalable workflow automation.

Design and orchestrate large-scale LLM pre-training across 1,000+ GPUs using PyTorch, DeepSpeed, or Megatron-LM. Optimize InfiniBand/RDMA networking and memory to avoid OOM, automate checkpointing and failure recovery for month-long runs, and manage SLURM or Kubernetes GPU clusters. Implement systems-level improvements using C++, CUDA, and Python.

Conduct research developing foundation models for robotics, align text-based reasoning with low-level control policies, design experiments evaluating zero-shot generalization, integrate models into robotic applications with interdisciplinary teams, and present findings at conferences.

Lead product strategy and roadmap to convert advanced AI and robotics research (e.g., VLA models, agentic RAG) into customer solutions. Define safety, usability, and performance metrics, engage early enterprise adopters for feedback, and coordinate cross-functional teams to deliver hardware and deep-tech software products.

Design MAPF algorithms, build low-latency Robot-to-Cloud and Robot-to-Robot communication, and develop cloud dashboards for fleet monitoring and teleoperation handoffs to optimize robotic fleet efficiency.

Design and implement functional safety systems for robotic products ensuring compliance with ISO 13849 and ISO 3691-4. Implement redundant safety-rated PLCs and collision-avoidance logic. Perform rigorous FMEA on hardware and software and support systems engineering and testing.

Design and implement Visual-Inertial SLAM pipelines, develop dynamic obstacle avoidance and predictive path-planning, and optimize navigation algorithms for low-compute edge deployment on robotic platforms.

Build and operate MLOps and agentic infrastructure: manage model registries, continuous training loops, and A/B testing; deploy agent microservices on Kubernetes; and create observability dashboards tracking token usage, latency, and agent reasoning.

Develop intent-recognition models from gaze, gesture, and voice data; implement socially aware navigation that respects personal space; and design visual and auditory feedback for robot user interfaces. Run user studies and rapidly prototype AI-driven voice and visual interfaces.