Director of AI Workload Intelligence

SK hynix America

$250K — $300K *
Enterprise Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Proven experience leading global AI system architecture initiatives and cross-functional teams.
  • Hands-on experience in AI inference systems, ML systems, and LLM serving.
  • Strong understanding of Transformers, LLMs, MoE, and multimodal inference.
  • Experience with AI frameworks including PyTorch, ONNX Runtime, and Triton Inference Server.
  • Knowledge in analyzing latency, throughput, and memory usage for AI workloads.

Responsibilities

  • Lead global collaboration on AI workload-based HBF technology, from research to productization.
  • Analyze AI models and trends to assess HBF applicability.
  • Classify relevant memory objects for HBF integration.
  • Define criteria for data placement and caching decisions.
  • Evaluate HBF integration within various AI frameworks.
  • Identify AI model families suitable for HBF.
  • Develop taxonomy for memory use and HBF applicability.

Benefits

  • Top-tier health insurance at no employee cost.
  • Comprehensive paid time off including holidays and parental leave.
  • 401k matching contributions.
  • Flexible Spending Accounts for health and dependent care.
  • Educational reimbursement of up to $10,000 annually.
  • Donation matching and volunteering opportunities.
  • Corporate discounts available.
  • Complimentary meals provided throughout the workday.
Full Job Description
Work Model: Onsite

Job Title: Director of AI Workload Intelligence
Office Location: San Jose, CA
Job Type: Full-Time
Work Model: Onsite

Job Summary:

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.

Responsibilities:
  • 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.

Qualifications:
  • 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.

Benefits:
  • Top Tier health insurance at no employee cost
  • Paid day offs: Paid Time Off, Company Holidays, Parental Leave, Happy Fridays
  • 401k Matching
  • Flexible Spending Account (FSA) for Health Care & Dependent Care
  • Educational reimbursement up to $10,000 per year
  • Donation Matching and volunteering opportunities
  • Corporate discount programs
  • Free Breakfast/Lunch/Dinner provided to employees


Compensation:

Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets. Pay within the provided range varies by work location and may also depend on job-related skills and experience. Your Recruiter can share more about the specific salary range for the job location during the hiring process.

Pay Range

$250,000-$300,000 USD

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