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# Researcher - Efficient AI

- **Company:** Microsoft
- **Location:** San Francisco, CA, United States
- **Experience:** Expert
- **Salary:** $119,800.0 - $234,700.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Microsoft Online Services, C++ (Programming Language), Software Quality, Nvidia CUDA, Software Debugging, Python (Programming Language), Open Source Technology, Tensorflow, Pytorch, Large Language Models, Parallel Computation, Gpu Programming, ONNX (Open Neural Network Exchange) Format, TensorRT
- **Published:** June 13, 2026
- **Apply:** https://www.dice.com/job-detail/be515d27-dada-48fb-a9fe-cce534009f38

## About the Role

* Doctorate in relevant field OR Master's Degree in relevant field AND 3+ years related research experience OR Bachelor's Degree in relevant field AND 4+ years related research experience OR equivalent experience.

Other Requirements:
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:

 * Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter., * Demonstrated experience in designing and optimizing efficient inference systems, combining foundations in algorithmic optimization, parallel computing, and request orchestration under strict SLO constraints with deep knowledge of attention and KV-cache optimizations, batching and scheduling strategies, and cost-aware deployment.
 * 3+ years of experience with machine learning frameworks (e.g., PyTorch, TensorFlow) and inference serving frameworks (e.g., vLLM, Triton Inference Server, TensorRT-LLM, ONNX Runtime, Ray Serve, DeepSpeed-MII).
 * 3+ years of experience in GPU programming and optimization, with expert knowledge of CUDA, ROCm, Triton, PTX, CUTLASS, or similar GPU programming frameworks.
 * Proficiency in C++ and Python for high-performance systems, with code quality and profiling/debugging skills
 * Research impact through publications and/or patents, coupled with hands-on experience taking research ideas through execution and delivery in production.

## Description

* Formulate, develop, and evaluate new algorithmic and system-level approaches for end-to-end AI serving, using analytical modeling and large-scale measurement to study token-level latency, tail latency (p95/p99), throughput-per-dollar, cold-start behavior, warm pool strategies, and capacity planning under multi-tenant SLOs and variable sequence lengths.
 * Design and experimentally evaluate endpoint configuration and execution policies, including batching, routing, and scheduling strategies, tensor and pipeline parallelism, quantization and precision profiles, speculative decoding, and chunked or streaming generation, and drive the most promising approaches through robust rollout and validation into production.
 * Perform hardware- and kernel-aware optimization by collaborating closely with model, kernel, compiler, and hardware teams to align serving algorithms with attention/KV innovations and accelerator capabilities.
 * Build and benchmark experimental prototypes and large-scale measurements to validate research ideas and drive them toward production readiness; produce clear technical documentation, design reviews, and operational playbooks.
 * Publish research results, file patents, and, where appropriate, contribute to open-source systems and serving frameworks


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