Senior AI Software Architect

Overview

Do you want to be at the forefront of innovating the latest hardware designs to propel Microsoft's cloud growth? Are you seeking a unique career opportunity that combines technical capabilities, cross-team collaboration with business insight and strategy?

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.

In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.

Join the Systems Planning and Architecture (SPARC) team within Microsoft's Azure Hardware Systems and Infrastructure (AHSI) organization, the team behind Microsoft's expanding Cloud Infrastructure and for powering Microsoft's "Intelligent Cloud" mission. Microsoft delivers more than 200 online services to more than one billion individuals worldwide, and AHSI is the team behind our expanding cloud infrastructure. We deliver the core infrastructure and foundational technologies for Microsoft's cloud businesses including Microsoft Azure, Bing, MSN, Office 365, One Drive, Skype, Teams and Xbox Live.

We are seeking a highly skilled Senior AI Software Architect to join our team focused on model enablement and performance optimization for Maia accelerators. This role is ideal for someone with strong experience in PyTorch-based model development, quantization techniques, and parallelization strategies at the framework level. You will work closely with hardware and software teams to bring up models on Maia and ensure they run efficiently.

Responsibilities

Model Enablement:

• Port and optimize large-scale AI models (e.g., foundation models, diffusion models, YOLO) to run efficiently on Maia hardware.

• Integrate models using frameworks such as PyTorch, ONNX, vLLM, and SGLang.

Performance Optimization:

• Apply techniques like KV cache quantization (e.g., BF16 FP8), checkpointing, and re-sharding for efficient inference and training.

• Experiment with parallelism strategies (TP, PP) and analyze performance impacts across interconnects (NVLink vs PCIe).

Inference Stack Development:

• Collaborate on improving inference pipelines, including KV caching in sglang/vllm and performance tuning at the PyTorch level.

• Work with Triton kernels for basic operations (e.g., FP8 dequantization) and assist in kernel performance analysis.

Cross-Team Collaboration:

• Partner with hardware architects and kernel developers for co-design discussions.

• Communicate effectively with multiple stakeholders to align on performance goals and deliverables.

Qualifications

Required Qualifications:

• Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python 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

• Bachelor's Degree in Computer Science or Engineering.
• 3+ years of strong hands-on experience with PyTorch and model optimization techniques.
• Practical knowledge of quantization techniques like PTQ/QAT especially for KV cache quantization.
• Familiarity with parallelization strategies and distributed training concepts (e.g., sharding, allreduce).
• 2+ years of experience with AI inference stacks like SGLang/vLLM and performance profiling.
• Excellent problem-solving and communication skills; ability to work in a collaborative team environment.
• 3+ years of experience in Triton kernels and CUDA programming (basic understanding is acceptable but willingness to learn is essential).
• Experience with AI accelerator hardware and embedded systems.
• 3+ years of prior work on efficient model checkpointing, resharding scripts, and large-scale model deployments for serving at scale.

Software 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 $158,400 - $258,000 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
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This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

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