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Artificial Intelligence • Healthtech • Professional Services • Analytics • Consulting
The AI Engineering Specialist will oversee project tasks, manage expectations, mentor junior members, and design scalable AI systems while working with advanced AI models and ML pipelines.
Top Skills:
AWSAzureCloudFormationDatabricksDjangoDockerFast ApiJavaScriptKubernetesNext JsPythonReact JsTailwind CssTerraform
eCommerce • Healthtech • Pet • Retail • Pharmaceutical
Leads Chewy’s executive talent lifecycle, including executive onboarding, development, coaching, succession planning, readiness assessment, and leadership experiences. Partners with senior leaders, HR teams, and business stakeholders to design personalized executive programs, improve talent processes, strengthen leadership pipelines, and measure program effectiveness. Establishes governance, operating rhythms, tools, and playbooks to deliver a consistent, high-impact executive experience.
Artificial Intelligence • Internet of Things • Semiconductor
Design and build MLOps infrastructure for production deployment of data, machine-learning models, and software. Develop end-to-end ML pipelines, CI/CD/CT workflows, secure repository strategies, containerized deployments, and automation for Edge AI applications. Collaborate with developers, data scientists, and ML engineers to define tooling, monitor DevOps performance, and improve operational efficiency. Support embedded-system CI/CT, open-source pipelines, and model testing.
Top Skills:
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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.
We are looking for an AI Specialist Engineer to enhance the performance of large language and vision models for on-device inference. Your expertise will be crucial in developing and deploying cutting-edge AI solutions, ensuring optimal efficiency across diverse hardware architectures.
Responsibilities:
- Compress and optimize large language and vision models for on-device inference.
- Develop pipelines for model distillation and hardware-specific compilation.
- Benchmark performance across various NPU/GPU architectures.
Qualifications:
- Expertise in model distillation, pruning, and 4-bit/8-bit quantization techniques.
- Hands-on experience with TensorRT, ONNX Runtime, and edge deployment.
- Strong C++ and Python skills.
What you need to know about the Seattle Tech Scene
Home to tech titans like Microsoft and Amazon, Seattle punches far above its weight in innovation. But its surrounding mountains, sprinkled with world-famous hiking trails and climbing routes, make the city a destination for outdoorsy types as well. Established as a logging town before shifting to shipbuilding and logistics, the Emerald City is now known for its contributions to aerospace, software, biotech and cloud computing. And its status as a thriving tech ecosystem is attracting out-of-town companies looking to establish new tech and engineering hubs.
Key Facts About Seattle Tech
- Number of Tech Workers: 287,000; 13% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Amazon, Microsoft, Meta, Google
- Key Industries: Artificial intelligence, cloud computing, software, biotechnology, game development
- Funding Landscape: $3.1 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Madrona, Fuse, Tola, Maveron
- Research Centers and Universities: University of Washington, Seattle University, Seattle Pacific University, Allen Institute for Brain Science, Bill & Melinda Gates Foundation, Seattle Children’s Research Institute
