Applied Researcher I

Concord, New Hampshire
Jobs for Humanity
Job Description

Job Title: Applied Researcher I

Location: McLean, Virginia, United States of America

Overview:
At Capital One, we are using artificial intelligence (AI) to revolutionize banking and create trustworthy and reliable systems. Our AI and machine learning (ML) applications help us provide real-time, intelligent, and automated customer experiences, from detecting unusual charges to answering questions. We are looking for talented individuals to join our applied science and engineering teams and help us bring the power of AI to redefine how we serve our customers.

Team Description:
The AI Foundations team is at the core of bringing our AI vision to life at Capital One. We collaborate with academia, technology experts, and business leaders to apply the latest advancements in AI to our business.

In this role, you will:
– Work with a diverse team of data scientists, software engineers, machine learning engineers, and product managers to develop AI-powered products that transform how customers interact with their finances.
– Utilize a wide range of technologies, such as Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more, to uncover insights from large amounts of numeric and textual data.
– Build AI foundation models through all stages of development, from design to training, evaluation, validation, and implementation.
– Conduct impactful applied research to incorporate the latest AI developments into next-generation customer experiences.
– Effectively communicate complex concepts to business stakeholders and align your work with tangible business goals.

The Ideal Candidate:
– Has a passion for both analysis and decision-making that prioritizes our customers’ needs.
– Keeps up-to-date with emerging technologies and continuously evaluates their potential applications.
– Thrives in tackling big, undefined problems and enjoys asking and seeking answers to challenging questions.
– Challenges conventional thinking and strives to improve existing processes and practices.
– Has technical expertise and hands-on experience in developing AI models and solutions using open-source tools and cloud computing platforms.
– Demonstrates a deep understanding of AI methodologies and has experience with large deep learning models.
– Is experienced in delivering high-quality ideas or improving existing ideas in machine learning.
– Can independently pursue a research agenda and carry out long-term projects.

Basic Qualifications:
– Currently pursuing or holds a PhD, with an expected completion date on or before the scheduled start date. Alternatively, holds an M.S. degree with at least 2 years of experience in applied research.

Preferred Qualifications:
– PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering, or related fields.
– For specific focus areas (choose the set that applies to your expertise):
– Natural Language Processing (NLP): PhD focus on NLP or Masters with 5 years of industrial NLP research experience, multiple publications on pre-training of large language models, experience training a large language model from scratch, publications in deep learning theory, and publications in relevant conferences.
– Behavioral Models: PhD focus on geometric deep learning, papers on training models on graph and sequential data structures, experience scaling graph models, experience with deep learning-based recommender systems and real-time production environments, contributions to open-source frameworks, and experience with large datasets.
– Optimization (Training & Inference): PhD focused on optimizing training of very large deep learning models, multiple years of experience and/or publications on model sparsification, quantization, training parallelism/partitioning, gradient checkpointing, model compression, experience optimizing training for large models, in-depth knowledge of deep learning algorithmic design, and experience with compiler design.
– Finetuning: PhD focused on guiding language models with further tasks, knowledge of transfer learning principles and model adaptation, and experience deploying a fine-tuned large language model.
– Data Preparation: Publications on tokenization, data quality, dataset curation, or labeling, contribution to major open-source corpus, and contribution to open-source libraries for data quality, dataset curation, or labeling.

Salary Range:
The salary range for this role varies based on location. Please refer to the location-specific ranges below:
– New York City (Hybrid On-Site): $230,000 – $262,500 for Applied Researcher I
– San Francisco, California (Hybrid On-site): $243,700 – $278,100 for Applied Researcher I

Benefits:
Capital One offers a comprehensive and competitive set of health, financial, and other benefits to support your well-being. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. Learn more about our benefits on the Capital One Careers website.

Application Process:
We will accept applications for a minimum of 5 business days.

Equal Opportunity:
Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. We provide equal employment opportunities to all individuals regardless of sex, 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.

Accommodation and Support:
If you require an accommodation during the application process, please contact Capital One Recruiting at (phone number removed) or (url removed). We will ensure that your information is kept confidential and used only as necessary to provide