This role is flexible and offers a hybrid work model with three days per week in the office.
Microsoft's mission is to empower every person and every organization on the planet to achieve more. As employees, we come together with a growth mindset, innovate to empower others, and collaborate to achieve our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
Responsibilities
Develop and enhance analytical performance models and simulation frameworks for AI accelerators, GPU architectures, and large-scale AI systems.
Model end-to-end AI training and inference workloads, including compute kernels, attention, MoE, memory access patterns, and communication operations.
Evaluate new architectural features, compute and memory hierarchies, interconnects, and collective communication mechanisms to identify performance and efficiency improvements.
Perform workload mapping and parallelization analysis across tensor, pipeline, expert, data, and context parallelism strategies to optimize accelerator utilization and scalability.
Develop system-level performance models to evaluate throughput, latency, perf/W, and TCO across accelerator, rack, and cluster configurations.
Correlate analytical model predictions with silicon measurements, kernel benchmarks, and software traces to validate assumptions, improve model fidelity, and identify performance bottlenecks.
Build and automate performance modeling, design-space exploration, sensitivity analysis, and visualization tools to accelerate architectural evaluation.
Collaborate with hardware and software teams to translate modeling insights into actionable architecture recommendations and HW–SW co-design opportunities.
Qualifications
Required Qualifications
Master's Degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field AND 3+ years technical engineering experience OR Bachelor's Degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field AND 5+ years technical engineering 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.
Preferred Qualifications
Doctorate in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field AND 3+ years technical engineering experience OR Master's Degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field AND 6+ years technical engineering experience OR Bachelor's Degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field AND 8+ years technical engineering experience OR equivalent experience
Familiarity with AI agentic systems & flow for performance modeling & anlaysis
2+ years of experience in Computer Architecture, AI Systems, or closely related technical domains.
Strong understanding of GPU and AI accelerator architectures, including compute pipelines, memory hierarchies, interconnects, and parallel execution models.
Experience developing analytical performance models, roofline models, architectural simulators, or system-level performance estimation frameworks.
Knowledge of AI training and inference workloads, including transformers, attention mechanisms, MoE architectures, and large-scale distributed execution.
Experience modeling compute, memory bandwidth, communication collectives, and computation-communication overlap in accelerator-based systems.
Familiarity with parallelization strategies, including tensor, expert, pipeline, data, and context parallelism, and their performance implications.
Strong programming skills in Python and C/C++, with experience developing modeling frameworks, simulators, and performance analysis tools.
Experience with performance profiling, benchmarking, and correlation of analytical models with hardware measurements and software traces.
Familiarity with PyTorch, GPU programming, and modern AI inference or training frameworks such as vLLM, SGLang, and distributed runtime systems.
Experience evaluating architectural design trade-offs using performance, power efficiency, scalability, and TCO metrics.
Strong analytical, problem-solving, and communication skills, with the ability to translate performance insights into architectural recommendations.
Hardware Engineering IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $160,200 - $261,000 per year.
- Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
- https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.
