Applied Researcher 4 (AI Foundations - LLM, Optimization and Finetuning)
Capital One · McLean, VA · 1 mo ago
Analyst$219k–$250k/yrFull-time
We need to output HTML fragment with sections: Overview, Team Description, What You’ll Do, The Ideal Candidate (maybe split into subsections?), Basic Qualifications, Preferred Qualifications, Pay, Benefits? The posting includes salary ranges and mention of performance based incentive compensation, benefits. So we should include Pay section with salary ranges per location. Benefits: mention comprehensive benefits, but no specifics; we should not create Benefits section unless posting actually states them. It says "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 a statement about benefits, albeit vague. The instruction: "never create Pay/Schedule/Benefits sections unless the posting actually states them." It does state benefits generally, so we can include Benefits section with that statement. However we need to avoid filler like "commensurate with experience". This is okay.
We need to use for section headings. Use
for section headings. Use - for any list of duties/requirements/benefits. Use
for prose.
We must not repeat job title as heading. No Job ID. Remove boilerplate like EEO, legal, etc. Also remove application instructions, accommodation info, etc.
We need to preserve all substantive information. So we need to keep overview, team description, what you'll do, ideal candidate (maybe break into bullet points?), basic qualifications, preferred qualifications, pay, benefits, maybe note about performance based incentive compensation (could be part of Pay or Benefits). Also mention "Capital One will consider sponsoring a new qualified applicant for employment authorization for this position." That's substantive; maybe include in a paragraph under Overview or a separate section like "Work Authorization". But we need to decide sections: maybe Overview (includes first paragraph about trustworthy AI, team description, what you'll do). But we need headings for each section: About the role? The instruction says use
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we can use those headings. However we need to map content.
We have Overview paragraph: "At Capital One, we are creating trustworthy and reliable AI systems..." That's about the role/company. Could be "About the role". Then Team Description could be part of About the role or separate "Team Description". Could be "About the team". But we can follow typical headings: About the role, Responsibilities (What You’ll Do), Requirements (Basic Qualifications), Preferred Qualifications (maybe Skills), Benefits, Pay.
We also have "The Ideal Candidate" which is a list of attributes; could be under Skills or Requirements. We'll treat as Skills.
We need to ensure we don't create empty sections.
Let's extract content:
Overview: first 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: "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."
What You’ll Do: 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.
- Collaborate with senior researchers to prepare internal tech reports or conference submissions summarizing novel methods or findings
The Ideal Candidate: list of traits (Innovative, Creative, A leader, Technical) each with description. Could be formatted as - each trait with its description.
Basic Qualifications: "Currently has, or is in the process of obtaining, a 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 or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 2 years of experience in Applied Research"
Preferred Qualifications: list of many items: 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.
Also note: "Capital One will consider sponsoring a new qualified applicant for employment authorization for this position." This could be placed under a short paragraph maybe under Overview or a separate "Work Authorization" but we don't have a heading for that; we could incorporate into Overview or a note under Benefits? Probably better to add a short paragraph after Overview: "Capital One will consider sponsoring a new qualified applicant for employment authorization for this position."
Pay: salary ranges per location: Cambridge, MA: $218,700 - $249,600 for Applied Researcher 4; McLean, VA: $218,700 - $249,600 for Applied Researcher 4; New York, NY: $238,600 - $272,300 for Applied Researcher 4; San Jose, CA: $238,600 - $272,300 for Applied Researcher 4. Also note: "Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan."
We should include that in Pay section.
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 should not include EEO etc.
Now produce HTML fragment with headings
and content.
We need to decide which headings to use: About the role, Responsibilities, Requirements, Skills, Benefits, Pay. Could also include Team Description as part of About the role or separate heading "Team". But instruction says use those examples; we can add others if needed but better to stick to given list. We can embed Team Description inside About the role.
Thus:
About the role
Overview paragraph + team description + sponsorship note.
Responsibilities
- ... each bullet
Requirements
Basic Qualifications paragraph.
Skills
- ... each ideal candidate trait
Preferred Qualifications
- ... each preferred qualification item
Pay
Salary ranges per location + incentive note.
Benefits
Benefits paragraph.
We need to ensure we don't include any boilerplate like "No agencies please." etc.
Now craft the HTML.
We need to preserve all substantive information; ensure we don't lose any detail.
Let's write the About the role 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. 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. Capital One will consider sponsoring a new qualified applicant for employment authorization for this position."
That's all.
Now Responsibilities bullets: copy exactly.
Now Requirements: Basic Qualifications paragraph.
Now Skills: Ideal Candidate traits. We need to capture each trait with its description. Let's parse:
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 platformsHas a deep understanding of the foundations of AI methodologiesExperience 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, RLHFAn engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumesExperience in delivering libraries, platform level code or solution level code to existing productsA 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 projectsPossess the ability to own and
for prose. We must not repeat job title as heading. No Job ID. Remove boilerplate like EEO, legal, etc. Also remove application instructions, accommodation info, etc. We need to preserve all substantive information. So we need to keep overview, team description, what you'll do, ideal candidate (maybe break into bullet points?), basic qualifications, preferred qualifications, pay, benefits, maybe note about performance based incentive compensation (could be part of Pay or Benefits). Also mention "Capital One will consider sponsoring a new qualified applicant for employment authorization for this position." That's substantive; maybe include in a paragraph under Overview or a separate section like "Work Authorization". But we need to decide sections: maybe Overview (includes first paragraph about trustworthy AI, team description, what you'll do). But we need headings for each section: About the role? The instruction says use
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we can use those headings. However we need to map content.
We have Overview paragraph: "At Capital One, we are creating trustworthy and reliable AI systems..." That's about the role/company. Could be "About the role". Then Team Description could be part of About the role or separate "Team Description". Could be "About the team". But we can follow typical headings: About the role, Responsibilities (What You’ll Do), Requirements (Basic Qualifications), Preferred Qualifications (maybe Skills), Benefits, Pay.
We also have "The Ideal Candidate" which is a list of attributes; could be under Skills or Requirements. We'll treat as Skills.
We need to ensure we don't create empty sections.
Let's extract content:
Overview: first 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: "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."
What You’ll Do: 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.
- Collaborate with senior researchers to prepare internal tech reports or conference submissions summarizing novel methods or findings
The Ideal Candidate: list of traits (Innovative, Creative, A leader, Technical) each with description. Could be formatted as - each trait with its description.
Basic Qualifications: "Currently has, or is in the process of obtaining, a 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 or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 2 years of experience in Applied Research"
Preferred Qualifications: list of many items: 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.
Also note: "Capital One will consider sponsoring a new qualified applicant for employment authorization for this position." This could be placed under a short paragraph maybe under Overview or a separate "Work Authorization" but we don't have a heading for that; we could incorporate into Overview or a note under Benefits? Probably better to add a short paragraph after Overview: "Capital One will consider sponsoring a new qualified applicant for employment authorization for this position."
Pay: salary ranges per location: Cambridge, MA: $218,700 - $249,600 for Applied Researcher 4; McLean, VA: $218,700 - $249,600 for Applied Researcher 4; New York, NY: $238,600 - $272,300 for Applied Researcher 4; San Jose, CA: $238,600 - $272,300 for Applied Researcher 4. Also note: "Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan."
We should include that in Pay section.
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 should not include EEO etc.
Now produce HTML fragment with headings
and content.
We need to decide which headings to use: About the role, Responsibilities, Requirements, Skills, Benefits, Pay. Could also include Team Description as part of About the role or separate heading "Team". But instruction says use those examples; we can add others if needed but better to stick to given list. We can embed Team Description inside About the role.
Thus:
About the role
Overview paragraph + team description + sponsorship note.
Responsibilities
- ... each bullet
Requirements
Basic Qualifications paragraph.
Skills
- ... each ideal candidate trait
Preferred Qualifications
- ... each preferred qualification item
Pay
Salary ranges per location + incentive note.
Benefits
Benefits paragraph.
We need to ensure we don't include any boilerplate like "No agencies please." etc.
Now craft the HTML.
We need to preserve all substantive information; ensure we don't lose any detail.
Let's write the About the role 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. 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. Capital One will consider sponsoring a new qualified applicant for employment authorization for this position."
That's all.
Now Responsibilities bullets: copy exactly.
Now Requirements: Basic Qualifications paragraph.
Now Skills: Ideal Candidate traits. We need to capture each trait with its description. Let's parse:
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 platformsHas a deep understanding of the foundations of AI methodologiesExperience 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, RLHFAn engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumesExperience in delivering libraries, platform level code or solution level code to existing productsA 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 projectsPossess the ability to own and
and content.
We need to decide which headings to use: About the role, Responsibilities, Requirements, Skills, Benefits, Pay. Could also include Team Description as part of About the role or separate heading "Team". But instruction says use those examples; we can add others if needed but better to stick to given list. We can embed Team Description inside About the role.
Thus:
About the role
Overview paragraph + team description + sponsorship note.
Responsibilities
- ... each bullet
Requirements
Basic Qualifications paragraph.
Skills
- ... each ideal candidate trait
Preferred Qualifications
- ... each preferred qualification item
Pay
Salary ranges per location + incentive note.
Benefits
Benefits paragraph.
We need to ensure we don't include any boilerplate like "No agencies please." etc. Now craft the HTML. We need to preserve all substantive information; ensure we don't lose any detail. Let's write the About the role 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. 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. Capital One will consider sponsoring a new qualified applicant for employment authorization for this position." That's all. Now Responsibilities bullets: copy exactly. Now Requirements: Basic Qualifications paragraph. Now Skills: Ideal Candidate traits. We need to capture each trait with its description. Let's parse: 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 platformsHas a deep understanding of the foundations of AI methodologiesExperience 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, RLHFAn engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumesExperience in delivering libraries, platform level code or solution level code to existing productsA 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 projectsPossess the ability to own and