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AI SW Stack Deployment Architect (12+ years)

Sandisk Bengaluru, Indie
Pełny etat Praca stacjonarna

Data publikacji: 04.09.2026

Sandisk understands how people and businesses consume data and we relentlessly innovate to deliver solutions that enable today’s needs and tomorrow’s next big ideas. With a rich history of groundbreaking innovations in Flash and advanced memory technologies, our solutions have become the beating heart of the digital world we’re living in and that we have the power to shape.

Sandisk meets people and businesses at the intersection of their aspirations and the moment, enabling them to keep moving and pushing possibility forward. We do this through the balance of our powerhouse manufacturing capabilities and our industry-leading portfolio of products that are recognized globally for innovation, performance and quality.

Sandisk has two facilities recognized by the World Economic Forum as part of the Global Lighthouse Network for advanced 4IR innovations. These facilities were also recognized as Sustainability Lighthouses for breakthroughs in efficient operations. With our global reach, we ensure the global supply chain has access to the Flash memory it needs to keep our world moving forward.

Role Overview

We are looking for a Software Architect (12+ years experience) to lead the application/framework layer and deployment stack for the Next Generation Accelerator AI platform. This role owns how models run on Next Generation Accelerator—from vLLM / PyTorch / TensotFlow/XLA to production deployment—ensuring correctness, performance, and scalability.

Impact

Own customer-visible AI execution and deployment on Next Generation Accelerator , closing the gap between models and system performance , and enabling enterprise-grade AI solutions

Preferred Qualifications

Experience in distributed or multi-agent AI systems

Responsibilities

Architect integration of vLLM, PyTorch, and TensorFlow, JAX/XLA into Next Generation Accelerator stack; Define framework → compiler → runtime APIs and contracts; Own LLM execution behavior (batching, KV cache, streaming inference); Design and implement end-to-end deployment workflows (packaging, versioning, reproducibility); Drive performance optimization across model → framework → runtime; Work cross-functionally with compiler, runtime, and low-level SW teams; Support customer workloads, model onboarding, and debugging

Requirements

10+ years in AI/ML systems or software architecture; Strong experience with PyTorch / Transformers / LLMs; Hands-on experience with LLM deployment and scalable inference engine systems e.g. vLLM, Triton, SGLang etc.; Experience building scalable AI platforms (cloud/edge); Expertise in system design, APIs, and cross-layer integration

Nice to have

Experience with vLLM or similar LLM serving systems; Familiarity with XLA / MLIR / compiler frameworks; Exposure to AI accelerators (GPU/NPU) and runtime systems
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