Microsoft is looking to solve complex challenges in computing, healthcare, economics, and the environment by advancing machine learning (ML) systems for next-generation Artificial Intelligence (AI) workloads at Azure scale. The goal is to shape how Microsoft designs and deploys efficient and performant ML infrastructure, influencing compute platforms, acceleration strategies, and system-level optimizations.
Requirements
- Completed at least 2 academic courses or projects involving machine learning systems.
- At least 3 years of experience programming in Python, C++, or a similar systems-oriented language through work, projects, or research.
- Demonstrable Contribution to open-source ML framework or ML systems software.
- Deep and strong understanding of transformer-based model architectures, including attention mechanisms, KV cache behavior, and common training and inference bottlenecks.
- Experience with modern ML frameworks and runtimes such as PyTorch, Hugging Face Transformers, SGLang, vLLM, or TensorRT-LLM.
- Experience with GPU or accelerator programming using CUDA, Triton, or similar tools, and familiarity with profiling and performance analysis.
- Familiarity with benchmarking and performance profiling tools for ML workloads.
Responsibilities
- Contribute to research and exploration in advanced machine learning (ML) systems, focusing on the numeric, data types, and compute technologies that drive the next generation of Artificial Intelligence (AI) workloads at Azure scale.
- Collaborate across Azure teams to investigate cutting-edge approaches in model efficiency ranging from low-precision formats, quantization strategies, and ML kernel development, to benchmarking and analyzing emerging model architecture and hardware capabilities.
- Evaluate, prototype, and analyze new algorithmic and numerical techniques that improve the performance, cost, and efficiency of training and inference for large-scale models.
- Develop expertise in ML systems, emerging data types, kernel optimization, and performance modeling.
- Gain hands-on experience with the latest Azure AI and hardware technologies.
- Present findings from research and development strides.
- Contribute to the vibrant life of the research community.
Other
- Currently enrolled in a master’s, or PhD program in Computer Science, Electrical Engineering, or a related STEM field.
- Research Interns are expected to be physically located in their manager’s Microsoft worksite location for the duration of their internship.
- In addition to the qualifications below, you’ll need to submit a minimum of two reference letters for this position as well as a cover letter and any relevant work or research samples.
- During the 12-week internship, Research Interns are paired with mentors and expected to collaborate with other Research Interns and researchers, present findings, and contribute to the vibrant life of the community.
- Proficient analytical and problem-solving skills, with an interest in ML systems and computational performance.
