Senior Technical Program Manager II, AI/ML

We need to output HTML fragment with sections: headings using

for section headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We need to include only sections with real content. The posting includes Minimum qualifications, Preferred qualifications, About The Job (description), Responsibilities, Pay (Individual pay...), Benefits? It mentions "benefits" but no specifics; there is a line "Learn more about benefits at Google ." That's not specific benefit details, just a link. According to rules: never create Benefits section unless posting actually states them. It only says "Learn more about benefits at Google." That's not specific benefit content, so we should not create a Benefits section. Pay: they give salary range and bonus target etc. So we can create a Pay section with that info. Schedule: not mentioned, so omit. We need to include Minimum qualifications and Preferred qualifications maybe under Requirements or Qualifications. The instruction: Use headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We can decide which to use. We have content: About the job description (About The Job). Responsibilities section. Minimum qualifications and Preferred qualifications could go under Requirements or Qualifications. Since we have both minimum and preferred, we could combine into a Qualifications section with subpoints? But we must use

• for any list of duties/requirements/benefits. So we can list qualifications as list items. We also have Skills mentioned in preferred qualifications: "Excellent organizational, investigative, prioritization, communication and influencing skills. Ability to quickly learn..." etc. Those are skills. Could put under Skills section. We need to preserve all substantive information; do not invent or summarize away detail. So we need to include all details from the posting. Let's extract: Minimum qualifications: - Bachelor's degree in a technical field, or equivalent practical experience. - 10 years of experience in program management. - Experience with artificial intelligence/machine learning projects, tools, or infrastructure. - Experience with capacity management in a cloud environment. - Experience in Technical Program Management, Partner Management, and Release and Launch Readiness. Preferred qualifications: - Master's degree in Computer Science or a related technical field. - 10 years of experience managing complex cross-functional or cross-team projects. - Experience in a Site Reliability Engineering role. - Ability to quickly learn and understand the technical context of programs you drive and to contribute to technical discussions that affect the programs. - Excellent organizational, investigative, prioritization, communication and influencing skills. - Ability to manage multiple concurrent complex interactions with geographically disparate teams. About The Job (description): Long paragraph about Google's projects, role as Technical Program Manager, leading complex multi-disciplinary engineering projects, plan requirements, manage schedules, identify risks, communicate to stakeholders, explain analyses to executives, discuss technical trade-offs with engineers, manage projects of various size and scope, identify future opportunities, improve processes, drive technical directions. As a Senior Technical Program Manager in Labs/GDM-SRE, drive operational excellence at forefront of AI innovation, lead launch coordination, reliability standards, ML/compute capacity procurement for fast-growing Labs products in partnership with senior stakeholders, help scale GDM SRE 'Launch Control' model support rotation across DeepMind to ensure seamless reliable releases at scale. The AI and Infrastructure team redefining what's possible, empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Customers include Googlers, Google Cloud customers, billions of Google users worldwide. Driving force behind Google's groundbreaking innovations, empower development of cutting-edge AI models, delivering unparalleled computing power to global services, providing essential platforms that enable developers to build the future. From software to hardware teams shaping future of world-leading hyperscale computing, key teams working on development of TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more. Responsibilities: - Lead cross-functional launch readiness for Labs and GDM dependencies. - Standardize release playbooks, traffic ramp strategies, and bridge product, research, and SRE teams to seamlessly transition experimental prototypes into Google-scale products. - Partner with engineering to enforce operational requirements like Service Level Objectives (SLOs) and failover architectures. - Anticipate failure modes through readiness drills, rollback strategies, and post-launch reviews. - Manage the capacity life-cycle for machine learning (ML) accelerators and traditional compute across both rapidly scaling models and early-stage experiments. - Collaborate with SRE and Product engineers to eliminate operational bottlenecks by building tooling for quota tracking, launch management, and readiness verification. - Provide senior leadership with data-driven launch updates, capacity runway forecasts, risk assessments, and clear escalation pathways. Pay: - Individual pay is determined by factors including job-related skills, experience, and relevant education or training. - US: $240000 - $333000 (USD) + 25% bonus target + equity + benefits We should not include boilerplate like EEO etc. We need to output only HTML fragment, no /, no markdown fences. We'll create sections:

  About the role

  with the About The Job paragraph(s). Could be multiple

  but we can combine into one

  with line breaks? Better to keep as

  for each paragraph. We have a long description; we can split into maybe two paragraphs for readability but not required. We'll keep as one

  containing the whole description.

  Responsibilities

  with
  • items.

    Qualifications

    maybe split into Minimum and Preferred? Could have two subheadings? But only allowed headings are the listed ones; we could use

    Minimum qualifications

    and

    Preferred qualifications

    but those are not in the list. The instruction: use

    for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It says e.g., not exclusive list? It says use

    for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). Likely we should stick to those headings. So we can use

    Qualifications

    and inside list both minimum and preferred. Or we could use

    Requirements

    for minimum and

    Skills

    for preferred skills. But we have both minimum and preferred qualifications; we could put all under Qualifications. We also have Skills section: we could extract skills from preferred qualifications: ability to quickly learn..., excellent organizational..., ability to manage multiple concurrent... Those are skills. Could put under Skills. But we risk duplicating content. Better to put all qualifications under Qualifications, and maybe Skills separate for the skill-based items. Let's decide: - About the role: description. - Responsibilities: list. - Qualifications: list of minimum and preferred qualifications (including education, experience, etc.) - Skills: list of skill-based abilities (ability to quickly learn..., excellent organizational..., ability to manage multiple concurrent...) - Pay: paragraph with salary range etc. We must not create sections with filler. Ensure each section has real content. Now, we need to preserve all substantive information. If we split qualifications and skills, we need to ensure we don't lose any info. Let's list all items from minimum and preferred: Minimum: 1. Bachelor's degree in a technical field, or equivalent practical experience. 2. 10 years of experience in program management. 3. Experience with artificial intelligence/machine learning projects, tools, or infrastructure. 4. Experience with capacity management in a cloud environment. 5. Experience in Technical Program Management, Partner Management, and Release and Launch Readiness. Preferred: 1. Master's degree in Computer Science or a related technical field. 2. 10 years of experience managing complex cross-functional or cross-team projects. 3. Experience in a Site Reliability Engineering role. 4. Ability to quickly learn and understand the technical context of programs you drive and to contribute to technical discussions that affect the programs. 5. Excellent organizational, investigative, prioritization, communication and influencing skills. 6. Ability to manage multiple concurrent complex interactions with geographically disparate teams. Now, we could put items 1-3,4-5 under Qualifications (education/experience) and items 4-6 under Skills. But item 4 (Ability to quickly learn...) is a skill, item 5 is skills, item 6 is ability to manage multiple concurrent... also skill. Thus Qualifications list: Bachelor's degree..., 10 years program management, experience with AI/ML, capacity management cloud, experience in TPM/Partner Management/Release Launch Readiness, Master's degree..., 10 years managing cross-functional projects, SRE experience. Skills list: Ability to quickly learn..., Excellent organizational..., Ability to manage multiple concurrent... We need to ensure we don't miss any: also "Ability to quickly learn and understand the technical context of programs you drive and to contribute to technical discussions that affect the programs." That's a skill. Now, we also have the About The Job paragraph includes mention of driving operational excellence etc. That's covered. Now, we need to output HTML. We'll do:

    About the role

    Google's projects, like our users, span the globe and require managers to keep the big picture in focus while being able to dive into the unique engineering challenges we face daily. As a Technical Program Manager at Google, you lead complex, multi-disciplinary engineering projects using your engineering expertise. You plan requirements with internal customers and usher projects through the entire project lifecycle. This includes managing project schedules, identifying risks and clearly communicating them to project stakeholders. You're equally at home explaining your team's analyses and recommendations to executives as you are discussing the technical trade-offs in product development with engineers. Using your extensive technical and leadership expertise, you manage projects of various size and scope, identifying future opportunities, improving processes and driving the technical directions of your programs. As a Senior Technical Program Manager in Labs/GDM-SRE, you will drive operational excellence at the forefront of AI innovation. You will lead launch coordination, reliability standards, and ML/compute capacity procurement for fast-growing Labs products in close partnership with senior stakeholders, while helping to scale the GDM SRE 'Launch Control' model support rotation across DeepMind to ensure seamless, reliable releases at scale. The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide. We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.

    Responsibilities

    • Lead cross-functional launch readiness for Labs and GDM dependencies.
    • Standardize release playbooks, traffic ramp strategies, and bridge product, research, and SRE teams to seamlessly transition experimental prototypes into Google-scale products.
    • Partner with engineering to enforce operational requirements like Service Level Objectives (SLOs) and failover architectures.
    • Anticipate failure modes through readiness drills, rollback strategies, and post-launch reviews.
    • Manage the capacity life-cycle for machine learning (ML) accelerators and traditional compute across both rapidly scaling models and early-stage experiments.
    • Collaborate with SRE and Product engineers to eliminate operational bottlenecks by building tooling for quota tracking, launch management, and readiness verification.
    • Provide senior leadership with data-driven launch updates, capacity runway forecasts, risk assessments, and clear escalation pathways.

    Qualifications