AI & Machine Learning Engineering Consultant - Manager - Consulting - Location OPEN

We need to output HTML fragment with sections for headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. Must not repeat job title. No metadata like Job ID. Remove boilerplate. We need to parse the posting. Key parts: Location: Anywhere in Country (maybe ignore). Then intro paragraphs: At EY... etc. That's about the role? Could be "About the role". We'll include that as prose. Then "The opportunity" paragraph describing AI, Data & Engineering team, etc. Could be part of About the role. Then "Your Key Responsibilities As a Manager in Model Engineering..." then bullet list of responsibilities. Then "Skills And Attributes For Success" then paragraphs and bullet list of attributes. Then "To qualify for the role, you must have:" list of qualifications. Then "Ideally, you’ll also have:" list of preferred qualifications. Then "What We Look For" paragraph. Then "What We Offer You At EY..." includes benefits and salary range. We need sections: About the role (intro), Responsibilities (bullet list), Requirements (maybe qualifications?), Qualifications (maybe required?), Skills (skills and attributes), Benefits (what we offer), Pay (salary range), Schedule (none? Not mentioned). So we should not include Schedule if not present. We must not include sections with placeholder like "commensurate with experience". Not present. We need to preserve all substantive info, not invent or summarize away detail. So we need to include all details from the posting, but we can combine similar info. We must not repeat job title. No headings for Job ID. We need to use

for section headings. Use

• for any list of duties/requirements/benefits. Use

  for prose. We need to output only HTML fragment. Let's structure:

  About the role

  At EY, we’re all in to shape your future with confidence. We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. The opportunity Our AI, Data & Engineering team helps apply cutting edge technology and techniques to bring solutions to our clients. As part of that, you'll sit side-by-side with clients and diverse teams from EY to create a well-rounded approach to advising and solving challenging problems, some of which have not been solved before. No two days will be the same, and with constant research and development, you'll find yourself building knowledge that can be applied across a wide range of projects now, and in the future. You'll need to have a passion for continuous learning, stay ahead of the trends, and influence new ways of working so you can position solutions in the most relevant and innovative way for our clients. You can expect heavy client interaction in a fast-paced environment and the opportunity to develop your own career path for your unique skills and ambitions. In this role, you will research, build, and implement scalable AI, machine learning, generative AI, and agentic systems that learn, reason, and generate outputs tailored to business requirements across various environments, including cloud and on-premises. You will enhance data pipelines and storage, ensuring data is clean, accurate, and optimized for XOps processes. Additionally, you will monitor and evaluate learning processes to continuously improve high-performance models, collaborating with other data and analytics professionals to industrialize analysis into effective analytics solutions.

  That seems to capture the intro and opportunity. Next Responsibilities:

  Responsibilities

  • Leading AI workstreams from solution design through production deployment and ongoing optimization.
  • Continuously improving processes by identifying innovative solutions through research and analysis.
  • Managing multidisciplinary teams to deliver complex AI engineering initiatives, with accountability for quality, responsible deployment, and results.
  • Engaging actively with clients, participating in daily working sessions, and leading workstreams from planning through execution to closure.
  • Identifying opportunities for additional services and managing engagement economics.
  But also earlier responsibilities paragraph: "Your Key Responsibilities As a Manager in Model Engineering, you will play a pivotal role in delivering innovative solutions that drive business success. You will work with a wide variety of clients to deliver modern AI engineering, machine learning, and generative AI technologies. Your teams will design and build scalable solutions that unify, enrich, and derive insights from varied data sources across a broad technology landscape. You will help our clients navigate the complex world of modern data science, analytics, and software engineering. We'll look to you to provide guidance and perform technical development tasks to ensure AI solutions are responsibly engineered, evaluated, deployed, and maintained to support the ongoing business needs of our clients. You will be joining a dynamic and interdisciplinary team of scientists and engineers who love to tackle the most challenging computational problems for our clients. We love to think creatively, build applications efficiently, and collaborate in both the ideation of solutions and the pursuit of new opportunities. Many on our team have advanced academic degrees or equivalent experience in industry." We need to preserve all substantive info. So we should include that prose as part of Responsibilities maybe before the list. The instruction: Use

  for prose. So we can have a

  with that paragraph, then

  for the bullet list. Thus Responsibilities section:

  ... (the paragraph)

  then
  list. Next Skills And Attributes For Success: we need Skills section maybe. Also Requirements and Qualifications sections. We have "To qualify for the role, you must have:" list of required qualifications. That's Requirements/Qualifications. We could put Requirements for required qualifications, and Qualifications for preferred? But we need to decide. The instruction: Use headings for Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We need to include sections only if posting has real specific content. We have required qualifications list (Bachelor's degree, 6-10 years experience, etc). That's definitely content. We also have "Ideally, you’ll also have:" list of preferred qualifications. That could go under Qualifications (or maybe also under Requirements? but we can treat required as Requirements, preferred as Qualifications). Also we have "Skills And Attributes For Success" which includes both skills and attributes. That could go under Skills. We also have "What We Look For" paragraph about critical thinking etc. Could be part of Skills or maybe a separate section? Not a defined heading; we could incorporate into Skills section as prose. We also have "What We Offer You At EY..." includes benefits and salary range. So Benefits section for benefits (medical, dental, pension, 401k, paid time off). Pay section for salary range. Schedule not present. Thus we need sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay. Now we need to ensure we don't repeat info. Let's extract each. About the role: we already captured intro and opportunity paragraphs. Could also include the first paragraph about location? Location: Anywhere in Country - maybe we can include as a short p? But location is minor metadata; we could fold into a short p or drop. The instruction: do NOT put Job ID / requisition numbers as headings — fold minor metadata into a short

  or drop it. Location is minor metadata; we could include a short p at start maybe before About the role? But we already have About the role section; we could include location as a p inside that section? Might be okay. However we should not repeat job title. Location is not a heading. We'll include a short p:

  Location: Anywhere in Country

  maybe before About the role? But the instruction says fold minor metadata into a short

  or drop it. Could include as a p before the first heading. But we need to output only HTML fragment; we can have a p then h3 sections. Let's do:

  Location: Anywhere in Country

  About the role

  ... (intro)

  Now Responsibilities: include the paragraph about pivotal role etc, then bullet list. Now Requirements: required qualifications bullet list. Now Qualifications: preferred qualifications bullet list. Now Skills: include Skills And Attributes For Success paragraph and bullet list of attributes, plus What We Look For paragraph maybe. Now Benefits: paragraph about Total Rewards package: medical and dental coverage, pension and 401(k) plans, wide range of paid time off options. Now Pay: salary range details. Now we must not include Schedule. Check for any duplicated lines: we need to avoid repeating same content. Let's extract exact text. From posting: Location: Anywhere in Country Intro: "At EY, we’re all in to shape your future with confidence. We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world." Opportunity paragraph: "The opportunity Our AI, Data & Engineering team helps apply cutting edge technology and techniques to bring solutions to our clients. As part of that, you'll sit side-by-side with clients and diverse teams from EY to create a well-rounded approach to advising and solving challenging problems, some of which have not been solved before. No two days will be the same, and with constant research and development, you'll find yourself building knowledge that can be applied across a wide range of projects now, and in the future. You'll need to have a passion for continuous learning, stay ahead of the trends, and influence new ways of working so you can position solutions in the most relevant and innovative way for our clients. You can expect heavy client interaction in a fast-paced environment and the opportunity to develop your own career path for your unique skills and ambitions. In this role, you will research, build, and implement scalable AI, machine learning, generative AI, and agentic systems that learn, reason, and generate outputs tailored to business requirements across various environments, including cloud and on-premises. You will enhance data pipelines and storage, ensuring data is clean, accurate, and optimized for XOps processes. Additionally, you will monitor and evaluate learning processes to continuously improve high-performance models, collaborating with other data and analytics professionals to industrialize analysis into effective analytics solutions." We could combine the two paragraphs into one

  maybe with a space. Now Responsibilities paragraph: "Your Key Responsibilities As a Manager in Model Engineering, you will play a pivotal role in delivering innovative solutions that drive business success. You will work with a wide variety of clients to deliver modern AI engineering, machine learning, and generative AI technologies. Your teams will design and build scalable solutions that unify, enrich, and derive insights from varied data sources across a broad technology landscape. You will help our clients navigate the complex world of modern data science, analytics, and software engineering. We'll look to you to provide guidance and perform technical development tasks to ensure AI solutions are responsibly engineered, evaluated, deployed, and maintained to support the ongoing business needs of our clients. You will be joining a dynamic and interdisciplinary team of scientists and engineers who love to tackle the most challenging computational problems for our clients. We love to think creatively, build applications efficiently, and collaborate in both the ideation of solutions and the pursuit of new opportunities. Many on our team have advanced academic degrees or equivalent experience in industry." Then bullet list: - Leading AI workstreams from solution design through production deployment and ongoing optimization. - Continuously improving processes by identifying innovative solutions through research and analysis. - Managing multidisciplinary teams to deliver complex AI engineering initiatives, with accountability for quality, responsible deployment, and results. - Engaging actively with clients, participating in daily working sessions, and leading workstreams from planning through execution to closure. - Identifying opportunities for additional services and managing engagement economics. Now Requirements (required qualifications) bullet list: - A Bachelor’s degree required (4-year degree). - 6-10 years of relevant experience of full-time working experience in AI, Data Science, and/or Machine Learning - 2-4 years of experience directly managing technical teams - Strong skills in Python - Ability lead, collaborate, and communicate effectively with diverse, hybrid and global teams - Experience designing, building