AI System Performance Engineer

Intel Technology India Pvt Ltd; Bengaluru; Hybrid; INR 1,200,000 - 2,200,000; Full time

Job summary

Intel Technology India Pvt Ltd is seeking an AI System Performance Engineer in Bengaluru, India. The role focuses on building analytical models to project end-to-end system performance for AI training and inference, across serving strategies and interconnects, to identify bottlenecks and optimize configurations for Intel architecture.

The candidate will enable new AI workloads in simulators, model GPU architectures and deployment scenarios, and integrate/modify open-source models.

Qualifications

• BTech or MSc in Electrical/Computer Engineering, CS, or related field.
• 1+ years in AI workloads or GPU architecture modelling/simulation.
• Strong Python proficiency for modular analytical models.
• Solid understanding of GPU/CPU architecture and memory hierarchy.
• Knowledge of LLM workloads and kernel internals.

Responsibilities

• Enable new AI workloads in analytical simulators.
• Model multi-GPU deployment and parallelization strategies.
• Create performance estimates exposing bottlenecks.
• Integrate open-source simulators for Intel architecture.
• Perform what-if analyses across core counts and bandwidths.

Skills

Python

GPU modelling

AI workloads

Analytical modelling

Performance analysis

Education

BTech/MS in EE/CE/CS

Tools

Analytical simulators

Open-source simulators

Perf tools

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

Required 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

Work Model for this Role

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.