Industry not specified

Principal Software Engineering - Performance

at Microsoft

Tech LeadNo visa sponsorshipData Science/AI/ML

Posted 4 hours ago

No clicks

Compensation: $139,900 – $331,200 USD
City: San Francisco
Country: United States

Lead end-to-end inference performance optimization for OpenAI and other state-of-the-art LLMs, benchmarking on Nvidia/AMD GPUs and Microsoft silicon. Own performance improvements across kernels, models, algorithms and system-level components, and develop tooling to surface opportunities and reduce the computing fleet footprint. Design, implement and test AI/DNN/LLM frameworks and tools, enabling fast time-to-market for models and scalable deployments. This hands-on principal engineer role requires collaboration with internal and external partners, and is based in the SF Bay Area with remote options for strong candidates.

Overview

The Artificial Intelligence Cloud Inference team at Microsoft develops AI software that enables running AI models everywhere, from world’s fastest AI supercomputers, to servers, desktops, mobile phones, IoT devices and internet browsers. We collaborate with our hardware teams and partners, both internal and external, and operate at the intersection of AI algorithmic innovation, purpose-built AI hardware, systems, and software. We are a team of highly capable and motivated people that pride themselves on a collaborative and inclusive culture.

We own inference performance of OpenAI and other state of the art LLM models and work directly with OpenAI on the models hosted on the Azure OpenAI service serving some of the largest workloads on the planet with trillions of inferences per day in major Microsoft products, including Office, Windows, Bing, SQL Server, and Dynamics.

As a Principal Engineer on the team, you will have the opportunity to work on multiple levels of the AI software stack, including the fundamental abstractions, programming models, runtimes, libraries and APIs to enable large scale training and inferencing of models. You will benchmark OpenAI and other LLM models for performance on GPUs and Microsoft HW, debug and optimize performance at all levels of abstraction including kernel, model, algorithm and system level, monitor performance and drive efficiencies that contribute to achieving Microsoft Azure's capex goals.

This is a hands-on technical role requiring software design and development skills. We’re looking for someone who has a demonstrated history of solving technical problems and is motivated to tackle the hardest problems in building a full end-to-end AI stack. An entrepreneurial approach and ability to take initiative and move fast are essential.

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.

SF Bay Area preferred, remote locations considered for very strong candidates.

Responsibilities

As a Principal Software Engineer on the team the common tasks of the job would include, but not be limited to:

Identify and drive improvements to end-to-end inference performance of OpenAI and other state of the art LLMs
Measure, benchmark performance on Nvidia/AMD GPU's and first party Microsoft silicon
Optimize and monitor performance of LLMs and build SW tooling to enable insights into performance opportunities ranging from the model level to the systems and silicon level, help reduce the footprint of the computing fleet and achieve Azure AI capex goals
Enable fast time to market of LLMs/models and their deployments at scale by building SW tools that afford velocity in porting models on new Nvidia, AMD GPUs and Maia silicon
Design, implement, and test functions or components for our AI/DNN/LLM frameworks and tools
Speeding up/reducing complexity of key components/pipelines to improve performance and/or efficiency of our systems
Communicate and collaborate with our partners both internal and external
Embody Microsoft's Culture and Values

Qualifications

Required Qualifications:

Bachelor's Degree in Computer Science or related technical field 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.

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 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.
4+ years’ practical experience working on high performance applications and performance debug and optimization on CPU's/GPU's.
Technical background and solid foundation in software engineering principles, computer architecture, GPU architecture, HW neural net acceleration.
Experience in end-to-end performance analysis and optimization of state of the art LLMs, HPC applications including proficiency using GPU profiling tools.
Experience in DNN/LLM inference and experience in one or more DL frameworks such as PyTorch, Tensorflow, or ONNX Runtime and familiarity with CUDA, ROCm, Triton.

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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Industry not specified

Principal Software Engineering - Performance

at Microsoft

Tech LeadNo visa sponsorshipData Science/AI/ML

Posted 4 hours ago

No clicks

Compensation: $139,900 – $331,200 USD
City: San Francisco
Country: United States

Overview

SF Bay Area preferred, remote locations considered for very strong candidates.

Responsibilities

As a Principal Software Engineer on the team the common tasks of the job would include, but not be limited to:

Identify and drive improvements to end-to-end inference performance of OpenAI and other state of the art LLMs
Measure, benchmark performance on Nvidia/AMD GPU's and first party Microsoft silicon
Optimize and monitor performance of LLMs and build SW tooling to enable insights into performance opportunities ranging from the model level to the systems and silicon level, help reduce the footprint of the computing fleet and achieve Azure AI capex goals
Enable fast time to market of LLMs/models and their deployments at scale by building SW tools that afford velocity in porting models on new Nvidia, AMD GPUs and Maia silicon
Design, implement, and test functions or components for our AI/DNN/LLM frameworks and tools
Speeding up/reducing complexity of key components/pipelines to improve performance and/or efficiency of our systems
Communicate and collaborate with our partners both internal and external
Embody Microsoft's Culture and Values

Qualifications

Required Qualifications:

Bachelor's Degree in Computer Science or related technical field 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.

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 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.
4+ years’ practical experience working on high performance applications and performance debug and optimization on CPU's/GPU's.
Technical background and solid foundation in software engineering principles, computer architecture, GPU architecture, HW neural net acceleration.
Experience in end-to-end performance analysis and optimization of state of the art LLMs, HPC applications including proficiency using GPU profiling tools.
Experience in DNN/LLM inference and experience in one or more DL frameworks such as PyTorch, Tensorflow, or ONNX Runtime and familiarity with CUDA, ROCm, Triton.

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.