Applied Researcher I

Capital One National Association; San Jose (CA); On-site; USD 234,000 - 267,000; Full time

Job summary

An established industry player is seeking an Applied Researcher I to revolutionize banking through AI. In this role, you will collaborate with a dynamic team of data scientists and engineers to develop innovative AI solutions that enhance customer interactions. You will leverage cutting-edge technologies to analyze vast datasets and create transformative AI models. This position offers a unique opportunity to engage in high-impact research, pushing the boundaries of AI applications in banking. If you are passionate about AI and eager to make a meaningful impact, this role is perfect for you.

Qualifications

• PhD or M.S. with experience in Applied Research required.
• Experience with AI foundation models and large deep learning models.

Responsibilities

• Partner with cross-functional teams to deliver AI-powered products.
• Build AI foundation models through all phases of development.

Skills

Machine Learning

AI Methodologies

Deep Learning

Natural Language Processing (NLP)

Data Analysis

Research Skills

Interpersonal Skills

Education

PhD in Computer Science

M.S. in Applied Research

Tools

Pytorch

AWS Ultraclusters

Huggingface

Lightning

VectorDBs

Job description

NYC 299 Park Avenue (22957), United States of America, New York, New York

Applied Researcher I

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.

In this role, you will:

1. 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.
2. Leverage a broad stack of technologies — Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more — to reveal the insights hidden within huge volumes of numeric and textual data.
3. Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation.
4. Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences.
5. Flex your interpersonal skills to translate the complexity of your work into tangible business goals.

The Ideal Candidate:

1. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers.
2. 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.
3. 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.
4. 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.
5. 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.
6. Has a deep understanding of the foundations of AI methodologies.
7. 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.
8. An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes.
9. Experience in delivering libraries, platform level code or solution level code to existing products.
10. 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.
11. Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects.

Basic Qualifications:

1. Currently has, or is in the process of obtaining, a PhD, with an expectation that required degree will be obtained on or before the scheduled start date or M.S. with at least 2 years of experience in Applied Research

Preferred Qualifications:

1. PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields
2. LLM
3. PhD focus on NLP or Masters with 5 years of industrial NLP research experience
4. 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)
5. Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens)
6. Publications in deep learning theory
7. Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR
8. Optimization (Training & Inference)
9. PhD focused on topics related to optimizing training of very large deep learning models
10. Multiple years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression
11. Experience optimizing training for a 10B+ model
12. Deep knowledge of deep learning algorithmic and/or optimizer design
13. Experience with compiler design
14. Finetuning
15. PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning)
16. Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance
17. Experience deploying a fine-tuned large language model

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

New York, NY: $234,000 - $267,000 for Applied Researcher I

San Francisco, CA: $234,000 - $267,000 for Applied Researcher I

San Jose, CA: $234,000 - $267,000 for Applied Researcher I

Cambridge, MA: $214,500 - $244,800 for Applied Researcher I

McLean, VA: $214,500 - $244,800 for Applied Researcher I

This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law.