Director of AI Workload Intelligence

At SK hynix America, we are at the forefront of semiconductor innovation. As a global leader in HBM, DRAM, and NAND flash technologies, we develop the advanced memory solutions powering everything from advanced mobile technology to massive AI data centers. With major investments in the U.S. and a leading position in the global AI revolution, we build the critical infrastructure of the digital landscape and remain committed to sustainable operations. We invite innovative minds to be part of our journey. Here, you will be part of a collaborative team pioneering the next generation of memory technologies, expanding our market footprint, and defining the future of computing.

Focused on bridging AI intelligence with memory strategy, this Director-level position leads global initiatives to analyze LLM and multimodal workloads for HBF applicability. The leader will define data placement criteria, develop HBF-aware benchmark suites, and guide product strategy by translating model behaviors into concrete memory system values.

• →Lead global collaboration and drive AI workload-based HBF technology development from research to PoC and productization.
• →Analyze AI models, algorithms, and workload trends for HBF applicability.
• →Classify HBF-relevant memory objects such as weights, KV cache, activations, embeddings, adapters, and MoE experts.
• →Define model-level criteria for data placement, caching, prefetching, and offload decisions.
• →Analyze HBF integration points in vLLM, SGLang, TensorRT-LLM, PyTorch, and ONNX Runtime.
• →Identify HBF-applicable AI model families and inference data objects.
• →Develop memory-use taxonomy and HBF applicability criteria.
• →Provide model-driven inputs to Compiler/Runtime and AI Inference SW Stack teams.

• Proven experience leading global AI system architecture initiatives and cross-functional teams.
• Hands-on experience in AI inference systems, ML systems, LLM serving, AI model analysis, AI framework/runtime analysis, or heterogeneous accelerator software.
• Strong understanding of Transformers, LLMs, MoE, recommendation models, embedding/retrieval workloads, and multimodal inference.
• Experience with PyTorch, Hugging Face, vLLM, SGLang, TensorRT-LLM, ONNX Runtime, Triton Inference Server, or equivalent AI inference stacks.
• Experience in latency, throughput, token throughput, memory footprint, bandwidth, and data movement analysis.

SK hynix America is an Equal Employment Opportunity Employer. We provide equal employment opportunities to all qualified applicants and employees and prohibit discrimination and harassment of any type without regard to race, sex, pregnancy, sexual orientation, religion, age, gender identity, national origin, color, protected veteran or disability status, genetic information, or any other status protected under federal, state, or local applicable laws.

In compliance with federal law, SK hynix America also participates in the federal E-Verify program. Upon accepting an offer of employment, all newly hired individuals will be required to complete Form I-9, which includes verifying identity and legal authorization to work in the United States. Please review the official government posters detailing your rights and protections prior to applying:

• E-Verify Participation Poster (Bilingual English & Spanish)
• IER Right to Work Poster (English)
• IER Right to Work Poster (Spanish)