AI Validation, Workload Enabling and Tools Engineer

Job Title

AI Validation, Workload Enabling and Tools Engineer

Role Summary

Work with internal engineering teams and ecosystem partners to validate, enable, and optimize AI workloads on Intel platforms. Focus areas include accuracy validation, performance tuning, benchmarking, tooling, and workload enablement across cloud, edge, and client products.

Support product enablement, pre-silicon modeling, platform bring-up, and collaborate with customers and ISVs to drive ecosystem readiness.

Experience Level

Senior — 8–15 years of relevant industry experience as indicated in the posting.

Responsibilities

Primary responsibilities include validation, benchmarking, workload enablement, and tool/automation development for AI models on Intel hardware.

• Validate AI workloads on Intel architectures; evaluate and debug deep-learning models, kernels, and operators to maximize performance while preserving accuracy.
• Perform benchmarking, regression analysis, and algorithmic validation across multiple use-cases and frameworks.
• Develop prototype workloads, tools, and automation pipelines to accelerate performance tuning and validation workflows.
• Evaluate model performance and accuracy on competitor hardware to identify gaps and improvement opportunities.
• Engage with customers, ISVs, and internal development groups to drive enablement and ecosystem readiness.
• Translate workload findings into actionable architecture and product insights; support next-generation platform bring-up and product maturity efforts.

Requirements

Must-have technical skills and experience; degrees and fields of study are summarized separately under Education Requirements.

• Must-have: Deep ML/DL knowledge including LLM architectures, Transformers, attention mechanisms, low-precision datatypes (fp8/fp4), quantization techniques, inference serving, and open-source upstreaming.
• Must-have: Hands-on experience with ML/DL models and distributed training/inference using PyTorch, TensorFlow, vLLM/SGLang or similar frameworks.
• Must-have: AI workload enabling experience including accuracy debugging and performance optimization; strong performance debugging and numerical analysis skills.
• Must-have: Proficiency in Python (NumPy, SciPy, Pandas, PyTest) and solid Linux development/debugging experience (git, cmake, gdb, strace, perf); familiarity with Git/GitHub/Gerrit workflows and CI/CD automation.
• Must-have: Understanding of distributed systems, HPC/GPU scaling, MPI/torchrun/Fully Sharded Data Parallel/Tensor Parallel, and high-performance networking (Ethernet/InfiniBand).
• Must-have: Experience with Docker/Kubernetes, virtualization, performance benchmarking, and automation.
• Must-have: Strong analytical, problem-solving, and communication skills with ability to work across architecture, development, and validation teams.
• Nice-to-have: Experience with Agentic AI deployment, validation framework design for high-level frameworks (SGLang/vLLM), and exposure to pre-silicon modeling or product maturity efforts.

Education Requirements

Bachelor's or Master's degree in Computer Science, Electronics Engineering, Mathematics, or a related technical field is specified in the posting.

About the Company

Company: Intel Corporation

Headquarters: Santa Clara, California, USA

Intel Corporation is a leading multinational technology company known for its innovative semiconductor solutions, including microprocessors, artificial intelligence accelerators, and memory products. Headquartered in the United States, Intel focuses on cutting-edge technology and a collaborative working environment, driving advancements in semiconductor manufacturing to meet global demands. The company emphasizes professional development and aims to shape the future of technology through groundbreaking designs.