обновлено 8 дней назад
Distinguished Engineer - AI (AI Infrastructure)
266 050 - 396 000$
Мэтч & Сопровод
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Описание вакансии
Текст:
TL;DR
Distinguished Engineer - AI (AI Infrastructure): Architecting and shipping next-generation AI infrastructure and inference platforms for millions of requests with an accent on distributed systems, storage, networking, and secure multi-tenant serving. Focus on optimizing LLM and computer vision inference, designing Kubernetes-based orchestration, and solving latency, throughput, reliability, and consistency challenges at scale.
Location: San Jose, California, United States; hybrid working environment with in-office and/or in-person expectations.
Salary: $266,050–$396,000 per year, with final compensation based on location, qualifications, experience, and education.
Company
develops intelligent data infrastructure, unified storage, integrated data services, and cloud solutions for enterprise workloads including AI.
What you will do
- Architect and deliver next-generation AI infrastructure and inference platforms serving millions of requests.
- Define technology strategy, product architecture, long-term vision, and roadmaps for AI infrastructure and ONTAP software and systems.
- Design solutions across distributed storage, filesystems, databases, networking, security, and control and data planes.
- Partner with product management and engineering to deliver enterprise-grade products for AI and cloud workflows.
- Influence executives and engineering leaders, mentor senior and principal engineers, and raise the technical bar.
- Represent internally and externally as an authority on scalable AI infrastructure and distributed systems.
Requirements
- 15+ years of experience architecting fault-tolerant, low-latency distributed systems.
- Deep hands-on expertise in AI/ML inference engines such as TensorRT, vLLM, ONNX Runtime, and Triton.
- Experience with model optimization, LLM and computer vision serving, RAG pipelines, and production latency targets.
- Expertise in GPU/TPU orchestration, Kubernetes scheduling extensions, service mesh, API gateways, and heterogeneous compute scheduling.
- Experience with high-performance networking and data planes, including RDMA, DPDK, kernel bypass, and custom protocols.
- Experience securing multi-tenant ML infrastructure with isolation, encryption, key management, and fine-grained RBAC/ABAC.
Culture & Benefits
- Hybrid work environment supporting connection, collaboration, and culture.
- Health insurance, life insurance, retirement or pension plans, paid time off, and leave options.
- Performance-based incentives, employee stock purchase plan, and/or restricted stock units, subject to regional variation.
- Flexible environment supporting work-life balance, initiative, impact, and ownership.
Hiring process
- Applications are reviewed only when submitted through the company website.
- Some stages for selected roles may use AI tools to support application evaluation and candidate selection alongside human decision-making.
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