Lead Applied AI ML for Payments

We need to output HTML fragment with sections: About the role? Actually the job description includes sections: Job Description (intro), Job Responsibilities, Required Qualifications..., Preferred Qualifications..., About Us, About The Team. We need to use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). We need to decide which headings to use based on content. We should not repeat job title as heading. No Job ID. Remove boilerplate: cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, application instructions. Also remove generic filler like "commensurate with experience" etc. The posting includes "We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location." That's vague; we should not create Pay section unless specific numbers. So we omit Pay. Benefits: they list benefits: comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. That's specific enough to create Benefits section. Schedule: not mentioned, so omit. We need sections: About the role (intro paragraph), Responsibilities, Requirements (maybe combine Required Qualifications and Skills?), Qualifications? The instruction list includes headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We can use those that have content. We have: About the role: the introductory paragraphs describing the role. Use

About the role

then

with the description. Responsibilities: list of responsibilities bullet points. Requirements: maybe combine Required Qualifications? Could be "Required Qualifications, Capabilities, And Skills". We'll put under

Requirements

with

• each bullet. Skills: maybe separate? But we could combine skills within Requirements. However we have Preferred Qualifications also. Could treat as

  Preferred Qualifications

  but not in list. The instruction says use those headings; but we can also add other headings if needed? It says "Use

  for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." It gives examples but not exclusive. Probably we should stick to those headings. So we need to map content to those headings. We have: About the role (intro). Responsibilities (list). Requirements (maybe required qualifications). Qualifications (maybe preferred qualifications?). Skills (maybe specific skills like Python, AWS, etc). Benefits (list). Pay (omit if not specific). Schedule (omit). We need to decide what goes where. Let's extract: Intro paragraph(s): "Join a team applying modern artificial intelligence and machine learning to high-impact, high-scale payments workflows. You will work with large datasets and complex operational processes to deliver measurable outcomes. You will build production-grade solutions spanning natural language processing, document understanding, and LLM-enabled applications. You will collaborate closely with business and technology partners to take ideas from concept to deployment. You will help raise engineering standards and mentor others while shipping real solutions. As an Applied AI/ML - Lead in Wholesale Payments Operations within Commercial & Investment Bank in JPMorgan Chase, you build and deliver enterprise AI/ML solutions that improve operational efficiency and decisioning. You partner with senior stakeholders to frame problems, define success metrics, and plan roadmaps. You design, implement, and deploy production services on Amazon Web Services (AWS) with strong engineering rigor. You establish model governance, monitoring, and responsible AI practices in line with risk and control requirements. You mentor engineers and lead reviews that improve quality, reliability, and delivery speed. Wholesale Payments supports global client payments across multiple methods, currencies, and geographies. The role focuses on building scalable AI/ML capabilities for operations use cases, including document processing and workflow automation. You contribute to reusable platforms and patterns that enable teams to safely deploy and operate models in production." That's the role description. Responsibilities bullet list: - Partner with senior business stakeholders to frame problems, define success metrics, and align AI/ML roadmaps to business priorities - Lead architecture, design, and end-to-end delivery of enterprise AI/ML solutions for Wholesale Payments Operations - Write clean, performant, production-quality code and set engineering standards across the team - Champion modern software development life cycle, continuous integration and continuous delivery, and DevOps practices - Deploy and operate AI/ML services on AWS at scale - Apply advanced techniques including data and text mining, document analysis, classification, optical character recognition (OCR), natural language processing (NLP), and LLM workflows (including retrieval-augmented generation and fine-tuning) - Design and implement scalable, secure data pipelines to support model training and inference - Define and enforce MLOps, model governance, monitoring, and responsible AI practices; represent the team in architecture and risk forums - Evaluate model performance in production, including drift management and reproducibility - Mentor engineers, conduct code and design reviews, and support recruiting and talent development Required Qualifications bullet list: - Master's degree in Mathematics, Computer Science, Engineering, or a related quantitative field - 6 years of professional AI/ML experience delivering production systems - 4 years of advanced Python development in production environments, including use of AI-assisted coding tools to improve productivity while preserving code quality - 4 years of hands-on experience designing and deploying production machine learning systems on Amazon Web Services (AWS) (for example: SageMaker, Lambda, ECS/EKS, S3) - Demonstrated experience delivering AI/ML solutions with measurable business outcomes at scale - Experience with object-oriented design, distributed systems, and performance engineering - Demonstrated experience building and deploying LLM-based applications, including retrieval-augmented generation and fine-tuning workflows - Hands-on experience in natural language processing (NLP), computer vision, optical character recognition (OCR), or document AI solutions in production - Experience implementing MLOps practices using tools such as MLflow, Kubeflow, Airflow, feature stores, or model registries - Demonstrated experience mentoring engineers and driving execution against multi-quarter roadmaps - Strong communication skills, including translating business needs into technical deliverables for senior stakeholders Preferred Qualifications bullet list: - Experience delivering AI/ML solutions in wholesale payments, transaction banking, or financial services - Experience with model risk management frameworks, model governance, and responsible AI practices - Experience with Kubernetes and infrastructure-as-code (for example: Terraform) - Experience with real-time or streaming inference use cases - Contributions to open-source machine learning ecosystems or peer-reviewed publications About Us paragraph: "JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans" We need to remove EEO/equal-opportunity boilerplate. So we should strip out the EEO statements. Also remove "Visit our FAQs for more information about requesting an accommodation." and the final line about Equal Opportunity Employer. Also remove "We recognize that our people are our strength..." maybe keep as part of About Us? It's not boilerplate but somewhat generic; but we can keep. However we need to remove duplicated lines and boilerplate. The EEO statements are boilerplate; remove them. Also remove "We also make reasonable accommodations..." that's part of EEO. Remove. Thus About Us should keep: description of firm, history, leader in various businesses, total rewards package description (but that's vague; we might not create Pay section). Benefits list we will extract to Benefits section. So About Us paragraph should be about the firm, not benefits. Thus About Us: "JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management." We could also keep the sentence about competitive total rewards package? That's vague; maybe we can keep but it's not specific; but it's not boilerplate. However we might avoid because it leads to Pay section. Safer to keep it? The instruction: "Prefer a few substantive sections over many thin ones." If we include that sentence, it's not specific pay; but we are not making a Pay section. It's okay to keep in About Us. But we also have Benefits section separate. Now About The Team paragraph: "J.P. Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world." We could include as part of About Us or separate section? Not in the heading list. Could be part of About Us or maybe we omit. The instruction says we can use those headings; but we can also add other headings if needed? It says "Use

  for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." It doesn't forbid other headings, but suggests using those. Safer to stick to those. So we could merge About The Team into About Us or omit. Since it's substantive, maybe include as part of About Us. Thus final sections:

  About the role

  ...

  Responsibilities

  ...

  Requirements

  ...
  (for Required Qualifications)

  Skills

  ...
  (maybe for Preferred Qualifications? Or we could put Preferred Qualifications under Skills. But Skills heading expects specific skills; we could list the preferred qualifications as skills. However we have many items like experience with Kubernetes, etc. That fits Skills. Alternatively we could have

  Qualifications

  for Preferred Qualifications. But we already used Requirements for required qualifications. We could have Qualifications for preferred. But the instruction list includes Qualifications as a heading separate from Skills. So we could do:

  Qualifications

  for Preferred Qualifications.

  Skills

  maybe for specific technical skills like Python, AWS, etc.