Applied Researcher 5 (AI Foundations, LLM Core and Agentic AI)

We need to output HTML fragment with sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. We need to parse the posting. Content: At Capital One, we are creating trustworthy... (intro). Team Description: The AI Foundations team... (maybe About the role). What You’ll Do: list of duties. The Ideal Candidate: bullet points describing ideal candidate (maybe Requirements/Qualifications/Skills). Basic Qualifications: list. Preferred Qualifications: list. Also mention salary ranges per location (Pay). Benefits: mention comprehensive benefits. Schedule: not mentioned. So we should include About the role (team description/intro), Responsibilities (What You’ll Do), Requirements (maybe Basic Qualifications), Qualifications (Preferred Qualifications?), Skills (maybe from Ideal Candidate bullet points). Benefits (mention comprehensive benefits). Pay (salary ranges). Schedule: not present, so omit. We must not repeat job title as heading. No Job ID etc. Remove boilerplate: EEO, accommodation, etc. Also remove application instructions like "No agencies please." etc. Also remove legal/EEO etc. We need to preserve all substantive information; do not invent or summarize away detail. So we need to keep the details: team description, responsibilities bullet list, ideal candidate bullet list (maybe as Skills?), basic qualifications bullet list, preferred qualifications bullet list, benefits statement, pay ranges. We need to use

for section headings. Use

• for any list of duties/requirements/benefits, and

  for prose. We need to decide which content goes where. Section headings allowed: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We need to map: - About the role: could be the introductory paragraph about Capital One AI Foundations team description. Possibly also team description. - Responsibilities: "What You’ll Do:" bullet list. - Requirements: maybe Basic Qualifications. - Qualifications: maybe Preferred Qualifications. - Skills: maybe The Ideal Candidate bullet list (innovative, creative, leader, technical, etc). Could also be part of Requirements but we have separate. - Benefits: mention comprehensive benefits. - Pay: salary ranges per location. - Schedule: not present, omit. We must not create sections with filler like "commensurate with experience". Not needed. We need to preserve all substantive info: So we need to include the bullet points exactly as given (maybe rephrase? but must preserve detail, not invent or summarize away). We can keep them as list items. We need to remove duplicated lines. There's some duplication? Not obvious. We need to remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. So we need to strip out the paragraphs about accommodation, EEO, drug-free workplace, criminal background, etc. Also remove "Capital One will consider sponsoring a new qualified applicant for employment authorization for this position." That's maybe substantive? It's about sponsorship; could be considered part of benefits? Might be considered substantive but it's about immigration sponsorship. Not sure if we should keep. The instruction says remove boilerplate; sponsorship might be considered substantive? It's not typical boilerplate but could be considered part of benefits. However it's not about benefits like health etc. It's about visa sponsorship. Might be considered part of the job posting details. The instruction says remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. Sponsorship is not explicitly listed; but it's not a standard benefit. Might keep? Safer to keep? However the instruction says preserve ALL substantive information; do NOT invent or summarize away detail. So we should keep sponsorship line if it's substantive. It's not boilerplate. So keep. Also "This role is also eligible to earn performance based incentive compensation..." that's substantive about compensation; could be part of Pay or Benefits. We'll include in Pay section maybe. Also "Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website." That's benefits. Also "Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level." That's benefits detail. Also "This role is expected to accept applications for a minimum of 5 business days." That's application instruction; should be removed. Also "No agencies please." remove. Also EEO statements etc remove. Also "Capital One promotes a drug-free workplace." remove. Also "Capital One will consider for employment qualified applicants with a criminal history..." remove. Also accommodation contact etc remove. Also technical support email etc remove. Also disclaimer about third-party products etc remove. Also note about Capital One Financial entities etc remove. Now we need to format. Let's extract sections. Intro paragraph: "At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build." Team Description: "Team Description: The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business." We could combine intro and team description under About the role. Now Responsibilities: "What You’ll Do:" then bullet list: - Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money. - Leverage a broad stack of technologies — Pytorch, AWS Ultraclusters, Huggingface, Lightning, and more — to reveal the insights hidden within huge volumes of numeric and textual data. - Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. - Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. - Flex your interpersonal skills to translate the complexity of your work into tangible business goals. - Lead cross-functional research threads that bridge prototype model development and deployment with ML engineering partners, ensuring scientific insights translate to production impact We need to keep the dash punctuation? Keep as is. Now Ideal Candidate bullet list (maybe Skills): - Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them - Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea - A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond - Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms - Has a deep understanding of the foundations of AI methodologies - Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF. - An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes - Experience in delivering libraries, platform level code or solution level code to existing products - A professional with a track record of coming up with high quality ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects - Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects We need to keep each bullet as

• . The bullet points have periods inside; we keep them. Now Basic Qualifications: - Currently has, or is in the process of obtaining, PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date plus 2 years of experience in Applied Research or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 years of experience in Applied Research We need to keep that as a single bullet? It's a sentence. Could be
• . Now Preferred Qualifications: multiple bullet points: - PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields - LLM - PhD focus on NLP or Masters with 5 years of industrial NLP research experience - Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization) - Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) - Publications in deep learning theory - Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR - Optimization (Training & Inference) - PhD focused on topics related to optimizing training of very large deep learning models - Multiple years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression - Experience optimizing training for a 10B+ model - Deep knowledge of deep learning algorithmic and/or optimizer design - Experience with compiler design - Finetuning - PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) - Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance - Experience deploying a fine-tuned large language model We need to keep each as separate
• . Some are short phrases; we keep. Now Benefits: "Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level." We could combine into a

  maybe. Also sponsorship line: "Capital One will consider sponsoring a new qualified applicant for employment authorization for this position." Could be part of Benefits or separate? Might be part of Benefits but it's about visa sponsorship. Could be included in Benefits

  . Now Pay: Salary ranges per location plus incentive compensation. We need to present Pay section: maybe a

  with the salary ranges. We need to include: "The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $262,500 - $299,600 for Applied Researcher 5 McLean, VA: $262,500 - $299,600 for Applied Researcher 5 New York, NY: $286,400 - $326,800 for Applied Researcher 5 San Jose, CA: $286,400 - $326,800 for Applied Researcher 5 Candidates hired to work in other locations will be subject to the