Group Engineer Manager - Windows ML Runtime & Tools

Overview

Help define how AI runs on Windows at global scale. The Windows AI Platform & Tools Team is building the foundational software that turns rapidly advancing models and silicon into fast, efficient, and trusted experiences for millions of customers. Working at the intersection of machine learning compilers, runtimes, operating systems, and heterogeneous hardware, you will lead teams collaborating across Microsoft and with leading silicon partners to solve some of the industrys most consequential edge-AI systems challenges.

As a Group Engineer Manager, you will lead Windows ML Runtime & Tools teams spanning Applied Science, Runtime, and MLIR. You will own the people, technical strategy, architecture, and execution needed to move innovations from research into durable Windows platform capabilities across CPU, GPU, and NPU hardware. You will build and grow high-performing teams while remaining deeply engaged in design quality, engineering systems, and cross-organization decisions. The organization will deliver developer tools, compiler and runtime capabilities, graph compilation, hardware-aware optimization, scheduling, memory orchestration, power efficiency, reliability, and secure execution. You will translate an ambitious platform vision into clear outcomes, develop managers and technical leaders, and align Windows, model, research, runtime, and silicon-partner teams to bring the next generation of local AI experiences to market. The role offers flexible work options, including partial remote work.

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.

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.

Responsibilities

• Managers deliver success through empowerment and accountability by modeling, coaching, and caring. Model: Live our culture. Embody our values. Practice our leadership principles. Coach: Define team objectives and outcomes. Enable success across boundaries. Help the team adapt and learn. Care: Attract and retain great people. Know each individual's capabilities and aspirations. Invest in the growth of others.
• Oversees partnership with appropriate internal (e.g., product manager, privacy/security subject matter expert, technical lead) and external (e.g. customer escalation team, public forums) stakeholders and leveraging expertise to anticipate, determine, and confirm customer/user requirements and their feasibility within and across teams for multiple solutions or product lines. Proactively seeks and leverages a variety of feedback channels to incorporate customer insights into future designs or solution fixes. Oversees team on incorporation of unwritten requirements, such as appropriate continuous feedback loops that measure actionable, quantitative (e.g., customer value, usage patterns, solution performance) and qualitative (e.g., accessibility, globalization) indicators of value. Determines additional critical metrics. Leads team in understanding and leading the provision of feedback on, and advocacy of the security and privacy needs of the customer who will be using the complex set of solutions.
• Oversees team and efforts, influences, and holds ownership of efforts and design discussions for overall system architecture of entire products/solutions that are deeply complex and often ambiguous. Looks for opportunities to leverage and incorporate open-source, off-the-shelf components and/or preexisting, managed services as part of the design of products/architecture. Oversees team on owning the testing and exploration of various design options for entire products/solutions, ensuring the strengths and weaknesses of each option are outlined and making recommendations for which design option is best. Owns creating proposals for architecture and design documents, and leads testing of hypotheses and deeply complex proposed solutions. Shares and acts on findings from investigations and owns design decisions and oversees the less experienced team members. Writes design documents that support user stories and other product requirements. Proactively identifies and evaluates new technologies to solve classes of problems, and determines and advocates for how to integrate these technologies within existing systems. Leads design discussions with the team and shares findings/learnings from investigations, owns design decisions. Provides technical and people leadership to ensure system architecture and individual designs meet performance, scalability, resiliency, disaster recovery, cost of goods sold (COGS), and other requirements and expectations. Holds teams accountable for upholding Microsofts standards of security, privacy, and other compliance requirements and expectations. Guides teams on understanding the importance of building solutions that expand upon the work of others. Leads the refinement of products through deeply complex data analytics and makes informed decisions in engineering products through data integration. Oversees team on reviewing deeply complex designs/architectures within and across teams to provide recommendations for improvements.
• Oversees team members within and across teams on producing extensible, maintainable, well-tested, secure, and performant code that adheres to design specifications. Leads efforts to continuously improve code performance, testability, maintainability, effectiveness, and cost, while accounting for and incorporating relevant trade-offs. Identifies best practices and coding patterns and provides deep expertise on the coding and validation strategy. Defines or reuses quality metrics, best practices, and coding patterns to ensure testable code. Leads by example in best code-writing practices (e.g., leveraging state-of-the-art generative artificial intelligence [GenAI], approaches to source code organization, naming conventions). Oversees team on leading efforts to identify and anticipate blockers or unknowns during the development process, escalate them, and communicate how they will impact timelines, and then driving the identification and implementation of strategies and/or opportunities to address them.
• Oversees teams on driving multiple groups project plans, release plans, and work items in coordination with appropriate stakeholders (e.g., technical program managers) across products. Develops the long-term project vision. Guides other teams on project estimation. Anticipates future goals to guide future resources. Reviews, implements, and recommends updates to resource management in response to changing context. Oversees teams on owning efforts to ensure required security protections and detection processes are accounted for in planning. Holds teams accountable for driving efforts to ensure project plans adhere to security, privacy, and compliance requirements. Holds teams accountable for proactively driving efforts to ensure all code across multiple products/solutions is properly flighted for quicker mitigation of production incidents. Acts as an expert and oversees team on calculating adequate capacity for planning, accounting for appropriate failover and backup/restore mechanisms for disaster recovery for a set of complex solutions. Establishes standards for teams for ensuring efficient operation of a set of complex products and/or solutions after it is live. Holds teams accountable for driving the proactive establishment of rollback plans for a set of complex products and/or solutions.
• Leads the resolution of complex site incidents and oversees for designated responsible individuals (DRI) and directs the work of other engineers across product lines. Oversees processes used to alert stakeholders to status and establishes actions to restore system/product/service. Reviews and approves proposed playbook. Coordinates people and resources to ensure DRI responsibilities are covered across teams. Ensures responses are within service level agreement (SLA) timeframe. Has line of sight to incidences and plans to address emerging issues. Leads efforts to reduce incident volume, looking globally at incidences and providing broad resolutions. Holds others accountable for ensuring overall DRI effectiveness and health across their teams.
• Champions skill development efforts to ensure engineering teams skills remain current by investing time and effort into being informed of current developments. Proactively seeks new knowledge, evaluating new trends, technical solutions, and patterns, assessing how to adapt them to current problems, and shares knowledge with other engineers. Oversees teams on conducting learning and literary sessions to raise awareness on relevant engineering design principles (e.g., security, testability, performance, scalability, accessibility, product knowledge).

Qualifications

Required Qualifications:

• Bachelors 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.

Preferred Qualifications:

• Masters Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python.

• OR Bachelors Degree in Computer Science or related technical field AND 15+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python.

• OR equivalent experience.

• 6+ years people management experience.

• Deep experience with MLIR, LLVM, ONNX Runtime, or comparable compiler and runtime technologies.

• Experience leading research and engineering teams that move machine learning innovations into production and optimize workloads for CPU, GPU, NPU, or other heterogeneous hardware.

• Demonstrated expertise in machine learning compiler design, graph optimization, memory management, scheduling, and performance analysis.

• Experience managing software engineers and developing high-performing technical teams.

• Experience leading architecture and delivery for machine learning research, developer tools, compilers, runtimes, machine learning infrastructure, systems software, or other performance-critical platform components.

• Experience driving complex technical initiatives and alignment across multiple engineering organizations.

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Software Engineering M6 - The typical base pay range for this role across the U.S. is USD $165,600 - $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.