Jobs

Member of Technical Staff, Multimodal Infrastructure - MAI Superintelligence Team
United States, California, Mountain View; United States, Washington, Redmond; United States, New York, New York
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On-site
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Full-time
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6d ago
Overview
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.
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 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 by jurisdiction.
Responsibilities-
Design, develop and maintain large-scale multimodal data processing pipelines.
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Design, develop and maintain large-scale multimodal model pretraining and post-training frameworks.
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Design, develop and maintain large-scale multimodal model inference and serving frameworks.
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Work with research scientists and product engineers to solve infra-related problems.
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Find a path to get things done despite roadblocks to get your work into the hands of users quickly and iteratively.
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Enjoy working in a fast-paced, design-driven, product development cycle.
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Embody our Culture and Values.
Qualifications:
Required Qualifications:
- 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 PythonOR equivalent experience
Preferred Qualifications:
- 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 PythonOR 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 Py Torch, 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, x DiT, 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
Software Engineering IC5 - The typical base pay range for this role across the U.S. is USD $139,900 - $274,800 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 $188,000 - $304,200 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
Software Engineering IC6 - The typical base pay range for this role across the U.S. is USD $163,000 - $296,400 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 $220,800 - $331,200 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.
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About Microsoft
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Pros
Excellent compensation and benefits package
Four-day workweek with improved work-life balance
Supportive managers and teams
Cons
High-pressure environment causing anxiety
Unprofessional interview processes
Limited creative work opportunities
Salary Ranges
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Junior/L3
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Bonus
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$156,314
$317,984
Interview Experience
7 interviews
Difficulty
3.7
/ 5
Duration
14-28 weeks
Offer Rate
14%
Experience
Positive 14%
Neutral 29%
Negative 57%
Interview Process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Technical Interview
5
Onsite/Virtual Interviews
6
Final Round
7
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