DC-GPU Performance Modeling Engineer
AMD · Hyderabad · 3+ yrs experience · Posted 2026-06-24
Tech stack: Python
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About the role
Architect, analyse and optimize high-performance GPU-centric SoCs for Machine Learning workload. Develop performance models and methodologies. Propose solutions to enhance performance and optimize power for next-generation data centre systems.
As a system performance architect on our design engineering team, you will help propose and implement solutions to our next generation GPU SoCs and optimize data centre system application performance.
Key
Responsibilities:
- Define, build and maintain performance models for performance projections, analysis and architecture exploration.
- Develop and execute system-level modelling strategies for ML and GPU hardware and software co-design.
- Drive performance trade-off studies for new architectural features, algorithms, and system configurations, providing data-driven recommendations.
- Collaborate with architecture, design and software teams to integrate models, define workloads and analyse simulation results.
- Innovate and advance modelling methodologies, tools and infrastructure to improve accuracy, speed, and architectural insight.
Qualifications:
- Strong understanding of computer architecture. Experience of working in GPUs, SoCs, ML accelerators would be a plus.
- Experience with performance analysis, workload characterization, and hardware/software co-design exploration.
- Familiarity with ML models and software stacks relevant to ML
- Understanding of AI model distributed training and inference, model layers and ML ops, parallelization strategies
- Experience in system-level modelling and simulation will be a plus.
- Strong programming skills, including experience with Python (or similar)
- Ph.D. in Computer Science / Electronics Engineering, and 3+ years of experience as a Performance Engineer
- M.S./M.Tech. in Computer Science / Electronics Engineering, and 5+ years of experience as a Performance Engineer
- B.Tech. in Computer Science / Electronics Engineering, and 7+ years of experience as a Performance Engineer
Qualifications
- Strong understanding of computer architecture.
- Experience of working in GPUs, SoCs, ML accelerators would be a plus.
- Experience with performance analysis, workload characterization, and hardware/software co-design exploration.
- Familiarity with ML models and software stacks relevant to ML
- Understanding of AI model distributed training and inference, model layers and ML ops, parallelization strategies
- Experience in system-level modelling and simulation will be a plus.
- Strong programming skills, including experience with Python (or similar)
- Ph.D. in Computer Science / Electronics Engineering, and 3+ years of experience as a Performance Engineer
- M.S./M.Tech. in Computer Science / Electronics Engineering, and 5+ years of experience as a Performance Engineer
- B.Tech. in Computer Science / Electronics Engineering, and 7+ years of experience as a Performance Engineer
Responsibilities
- Define, build and maintain performance models for performance projections, analysis and architecture exploration.
- Develop and execute system-level modelling strategies for ML and GPU hardware and software co-design.
- Drive performance trade-off studies for new architectural features, algorithms, and system configurations, providing data-driven recommendations.
- Collaborate with architecture, design and software teams to integrate models, define workloads and analyse simulation results.
- Innovate and advance modelling methodologies, tools and infrastructure to improve accuracy, speed, and architectural insight.