AI System Performance Engineer

Intel Corporation; Sarjapur; Hybrid; INR 1,200,000 - 2,700,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

Intel Corporation in Bangalore, India is seeking an AI System Performance Engineer to build analytical models of AI training and inference workflows. The role spans exploring GPU architectures, memory hierarchies, and interconnect behavior to identify bottlenecks and propose optimal configurations for Intel hardware.

You will work with simulators and open-source tools, implement what-if analyses, and contribute to performance projections across multi-GPU deployments.

Qualifications

• Strong Python skills to build analytical models and simulations.
• Background in computer architecture and GPU/CPU memory hierarchies.
• Experience with AI workloads and LLM deployments is a plus.
• 1+ years of AI workload or GPU architecture modelling experience.

Responsibilities

• Enable AI workloads in simulators and model multi-GPU deployment strategies.
• Create analytical models for GPU architectures and identify bottlenecks.
• Integrate open-source simulators and tailor them to Intel architecture.
• Perform what-if analyses across cores, memory, bandwidth to drive optimal configurations.

Skills

Python

GPU modelling

Analytical modelling

Simulation frameworks

LLM workloads knowledge

Education

BTech or MSc in EE/CE/CS

Tools

GitHub

CI/CD

Open-source simulators

Job description

Job Details: Job Description:

About the Role

We are looking for a talented and motivated AI System Performance Engineer. The role builds a strong understanding of AI training and inference systems and helps the team develop analytical models that project end-to-end system performance. Working across serving strategies, parallelism, collective communication, and interconnect behavior, the candidate uses these models to locate the architectural bottlenecks that limit performance and to recommend optimal system configurations for Intel architecture. A self-driven, hands-on learning by doing mindset and the ability to pick up unfamiliar workloads, tools, and architectures quickly are essential.

Key Responsibilities

• Enable new AI workloads in analytical simulators, and model emerging multi-GPU deployment, parallelization, and communication strategies as simulator capabilities.
• Build analytical models of newly proposed GPU architectures - GPU core, memory hierarchy, and training/inference deployment scenarios - and produce performance estimates that expose architectural bottlenecks and drive improvement recommendations.
• Integrate and modify open-source simulators or analytical models for Intel-specific architecture.
• Perform what-if analysis by sweeping core count, memory/cache capacity and bandwidth, fabric bandwidth, GPU interconnect, and deployment options; deliver optimization and optimal architecture recommendations.

Qualifications

• BTech or Master's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
• College graduate or 1+ years of experience in AI workload and GPU architecture modelling/simulation or a similar field.
• Strong proficiency in Python, with the ability to build modular, maintainable analytical models and simulation frameworks.
• In-depth understanding of computer architecture: GPU/CPU, ALU/SM core, cache, and different memory types and hierarchy.
• In-depth understanding of LLM AI workloads (Transformer, MoE, Attention, MLA - LLaMA, DeepSeek, Qwen, and robotic workloads) and kernel internals.

Good-to-Have Skills

• Understanding of distributed training/inference and parallelism strategies - data, pipeline, tensor, and expert - and their communication patterns when scaling across multi-GPU hardware.
• Understanding of LLM inference and training mechanics: prefill vs. decode, KV cache, batching policies, and quantization.
• Exposure to TRT-LLM, vLLM, or SGLang.
• Familiarity with Git/GitHub, CI/CD, and automated workflows.
• Understanding of power fundamentals and power/performance co-optimization.

Job Type: College Grad Shift: Shift 1 (India)

Primary Location: India, Bangalore

Additional Locations: Posting Statement: All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation or any other characteristic protected by local law, regulation, or ordinance.

Position of Trust N/A

This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site.

* Job posting details (such as work model, location or time type) are subject to change.

* ADDITIONAL INFORMATION: Intel is committed to Responsible Business Alliance (RBA) compliance and ethical hiring practices. We do not charge any fees during our hiring process. Candidates should never be required to pay recruitment fees, medical examination fees, or any other charges as a condition of employment. If you are asked to pay any fees during our hiring process, please report this immediately to your recruiter.