Multimodal Infrastructure

Microsoft AI is looking for a Member of Technical Staff, MultimodalInfrastructuretohelp build the next wave of capabilities of our personalized AI assistant, Copilot.We'relooking for someone who will bring an abundance of positive energy, empathy, and kindness to the team every day, in addition to being highly effective. The right candidate enjoys building world-class consumer experiences and products in a fast-paced environment. You will actively contribute to the development of AI models that are powering our innovative products. You will wear multiple hats and work on engineering, research, and everything in between. Your contributions will span model architecture, data curation, training and inference infrastructures, evaluation protocols, alignment and reinforcement learning from human feedback (RLHF), and many other exciting topics at thecutting edgeof AI.

Microsoft AI is building foundational models to develop novel responsible and efficient artificial general intelligence. The foundational models require large compute-capacity, and as a Member of Technical Staff-MultimodalInfrastructureyou would be responsible tobuild large-scale infrastructurestosupportthefullcycleofthemultimodalgenerativemodeldevelopmentin our innovative products. You will work closely with research scientists and product engineersonmultimodaldataprocessing, modeltraining,inferenceandservingtasks.As a contributing member of the core group of engineers, you would also bring to the table best practices driving architectural changes and influence roadmap of relevant software and hardware components. Your work will directlyimpactthe business goals of a wide range of users andfacilitatethe next wave of growth and innovation in AI.

Our newly formed organization, Microsoft AI, is dedicated to advancing Copilot and other consumer AI products and research. The teamis responsible forCopilot, Bing, Edge, and generative AI research.Come bea part of the team shaping the future personal computing.

Microsoft's mission is to empower every person and every organization on the planet to achieve more. Asemployees,we come together with a growth mindset, innovate to empower others, and collaborate to realize 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.

Starting January 26, 2026, MAI employees are expected to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.) or 25 miles (non-U.S., country-specific) of that location. This expectation is subject to local law and may vary byjurisdiction.

Responsibilities

• Design,developandmaintainlarge-scalemultimodaldataprocessingpipelines.

• Design, develop andmaintainlarge-scalemultimodalmodelpretrainingandpost-trainingframeworks.

• Design, developandmaintainlarge-scalemultimodalmodelinferenceand servingframeworks.

• Workwithresearchscientists andproductengineerstosolveinfra-relatedproblems.

• Finda path to get things done despite roadblocks to get your work into the hands of users quickly and iteratively.

• Bachelor's Degree in Computer Science, or related technical discipline AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python

• OR equivalent experience, * Bachelor's Degree in Computer Science or related technical field AND 10+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Master's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
• OR equivalent experience

• Experience in multi-modal data processing:

• Strong proficiency in distributed data processing infra (resource utilization management, fault tolerance, ray & spark) and CPU/GPU batch processing optimizations
• Experience with state-of-art model inference and serving frameworks
• Experience with image/video/audio data processing
• Experience with common data formats for efficient I/O

• Experience in multi-modal pretraining and post-training:

• Strong proficiency in deep learning frameworks such as PyTorch, Megatron and Deepspeed
• Knowledge of auto-regressive and diffusion transformer models
• Experience with distributed training techniques such as data parallelism, model parallelism, and pipeline parallelism
• Proven experiences in at least one of the following areas: image/video generation and editing; efficient architectures (e.g., MoE, window attention); efficient model design; or reinforcement learning training methods (e.g., RLHF, DPO, GRPO)

• Experience in multi-modal inference and serving:

• Strong proficiency in serving frameworks such as vLLM, TensorRT-LLM, SGLang, xDiT, Cache-DiT etc.
• Knowledge of distillation techniques such as Progressive Distillation, DMD, Self forcing etc.
• Knowledge of quantization and compression techniques like AWQ, GPTQ, and FP8 for multi-modal pipelines
• Experience in distributed inference scaling across multi-node clusters using Ray Serve and Triton
• Experience in leading technical projects and supporting architectural decisions with data

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