Ifm Us
Inference Optimization Intern – Performance Modeling
Sunnyvale, CA · Intern · Internship
Sponsorship not specifiedDetected 27 days ago
C++SassMachine LearningDeep LearningPyTorchNLPSystems EngineeringElectrical EngineeringResearchCommunication
About the role
- About the Institute of Foundation Models The Institute of Foundation Models is dedicated to advancing the science and engineering of large-scale AI systems.
- This internship provides hands-on experience in low-level GPU performance analysis, kernel optimization, and hardware-aware inference acceleration.
- This intensive internship offers a unique opportunity to contribute to the development of a simulator and profiling framework for foundation model inference on NVidia GPUs.
Responsibilities
- Develop analytical performance models for GPU kernels and inference workloads.
- Build and validate a simulator to estimate theoretical hardware performance limits.
- Collaborate with researchers and engineers to optimize inference kernels for transformer-based models.
- Design profiling methodologies for Hopper and Blackwell architectures.
- Document findings and provide actionable recommendations for performance improvements.
Requirements
- Currently pursuing a degree in Computer Science, Computer Engineering, Electrical Engineering, Artificial Intelligence, High-Performance Computing, or a related quantitative discipline.
Nice to have
- Experience with CUDA programming and GPU kernel development.
- Understanding of NVIDIA GPU architecture and memory hierarchy.
- Familiarity with performance profiling tools such as Nsight Systems and Nsight Compute.
- Knowledge of PTX, SASS, and low-level GPU execution.
- Experience optimizing CUDA kernels for throughput and latency.
- Understanding of roofline analysis, performance modeling, and hardware utilization metrics.
- Strong programming skills in C++, CUDA, and Python.
- Performance engineering mindset.
This listing is sourced directly from Ifm Us's careers page and normalized into a canonical job model.