Principal engineer, AI Serving Framework Architect (Software)

Confirmed live in the last 24 hours

Samsung Semiconductor

Compensation

$219,000 - $351,000/year

San Jose, California, United States

On-site

Posted April 8, 2026

Job Description

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Advancing the World’s Technology Together

Our technology solutions power the tools you use every day--including smartphones, electric vehicles, hyperscale data centers, IoT devices, and so much more. Here, you’ll have an opportunity to be part of a global leader whose innovative designs are pushing the boundaries of what’s possible and powering the future.

We believe innovation and growth are driven by an inclusive culture and a diverse workforce. We’re dedicated to empowering people to be their true selves. Together, we’re building a better tomorrow for our employees, customers, partners, and communities.

Job Title: Principal engineer, AI Serving Framework Architect (Software)

What You’ll Do

The Architecture Research Lab (ARL) focuses on addressing fundamental system-level bottlenecks in modern AI, particularly in memory capacity/bandwidth and system-scale communication. By leveraging Samsung’s world-class memory technologies, ARL explores and defines next-generation AI system architectures that deliver step-function improvements in performance, efficiency, and scalability.
We are seeking a Principal AI System Architect who will play a key role in bridging AI workloads, system architecture, and hardware design. In this role, you will develop system-level performance models, drive architecture-level design decisions, and propose forward-looking AI system architectures that shape Samsung’s long-term AI platform strategy.

Location: Daily onsite presence at our San Jose office in alignment with our Flexible Work policy

Job ID: 42853

As a Tech Lead, leading research teams in Korea and proposing technical direction
Research on dynamic scheduling methodologies for maximizing AI inference performance in multi-rack scale memory-centric systems, comprised of heterogeneous compute-capable memory and hierarchical memory
Investigating methods to accelerate search operations in RAG’s vector DB and AI Agent’s knowledge-graph by leveraging compute-capable memory
Studying strategies for optimally placing KVCache and a vector DB in hierarchical memory to minimize frequent SSD accesses and reduce IO stalls
Proposing SW design for implementing the derived optimization algorithms on open-source platforms such as vLLM

What You Bring

PhD in Computer Science or a related field with 10+ years of experience in AI Serving Framework for large-scale computing, with focusing on the AI workloads.
Led a project to build and optimize a Large Language Model (LLM) Inference Software Stack on a multi-rack scale system to deliver AI Inference services to over 100,000 users.
Extensive experience in designing AI Inference Software Stacks for heterogeneous devices.In-depth understanding of the internal architecture and operation mechanisms of inference engines such as vLLM.
Proficiency in AI Inference System Profiling and optimization.
Knowledge and practical experience with future AI workloads, including reasoning models, multi-modal solutions, AI agents, and world models.
Strong understanding of compute, memory, and networking bottlenecks in AI systems.
Required skillsets: PyTorch, Python, and C++
A collaborative mindset, curiosity, and resilience in solving complex challenges.
Excellent verbal, presentation, and written communication skills.
(Nice to have) Native or fluent Korean speakers are preferred.
You’re inclusive, adapting your style to the situation and diverse global norms of our people.
You approach challenges with curiosity and resilience, seeking data to help build. Understand