Member of Technical Staff, Multimodal Infrastructure Job at Microsoft Corporation (Mountain View)

Job Description

Microsoft AI is looking for a Member of Technical Staff, Multimodal Infrastructure to help build the next wave of capabilities of our personalized AI assistant, Copilot. We’re looking 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 the cutting edge of 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 – Multimodal Infrastructure you would be responsible to build large-scale infrastructures to support the full cycle of the multimodal generative model development in our innovative products. You will work closely with research scientists and product engineers on multimodal data processing, model training, inference and serving tasks. 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 directly impact the business goals of a wide range of users and facilitate the 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 team is responsible for Copilot, Bing, Edge, and generative AI research. Come be a part of the team shaping the future personal computing.

Job Responsibility

Design, develop and maintain large-scale multimodal data processing pipelines
Design, develop and maintain large-scale multimodal model pretraining and post-training frameworks
Design, develop and maintain large-scale multimodal model inference and serving frameworks
Work with research scientists and product engineers to solve infra-related problems
Find a path to get things done despite roadblocks to get your work into the hands of users quickly and iteratively
Enjoy working in a fast-paced, design-driven, product development cycle
Embody our Culture and Values

Requirements

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
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

Nice to have

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

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