Be an early applicantLess than 25 applicants

Company

Original Job Post

Capital One · 5 days ago

Sr. Director, Applied Research

San Francisco, CA

Full-time

Onsite

Director

$368K/yr - $420K/yr

Wonder how qualified you are to the job?

Maximize your interview chances

BankingCredit Cards

H1B Sponsorship

Actively Hiring

Comp. & Benefits

Insider Connection @Capital One

Discover valuable connections within the company who might provide insights and potential referrals, giving your job application an inside edge.

Responsibilities

Partner with a cross-functional team of scientists, machine learning engineers, software engineers, and product managers to deliver AI-powered platforms and solutions that change how customers interact with their money.

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.

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.

Flex interpersonal skills to translate the complexity of work into tangible business goals.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

People LeadershipLLMCore contributorNode clustersTraining optimizationBehavioral ModelsModel deploymentGraph modelsRecommender systemsReal-time environmentsOpen source frameworksInference learningOptimizationModel SparsificationQuantizationTraining ParallelismGradient CheckpointingModel CompressionFinetuningTransfer learningModel adaptationData PreparationData qualityDataset curationLeading contributionsOpen source libraries

Required

Ph.D. plus at least 6 years of experience in Applied Research or M.S. plus at least 8 years of experience in Applied Research

At least 5 years of people leadership experience

Preferred

PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields

LLM

PhD focus on NLP or Masters with 10 years of industrial NLP research experience

Core contributor to team that has trained a large language model from scratch (10B + parameters, 500B+ tokens)

Numerous publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR 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)

Has worked on an LLM (open source or commercial) that is currently available for use

Demonstrated ability to guide the technical direction of a large-scale model training team

Experience working with 500+ node clusters of GPUs Has worked on LLM scaled to 70B parameters and 1T+ tokens

Experience with common training optimization frameworks (deep speed, nemo)

Behavioral Models

PhD focus on topics in geometric deep learning (Graph Neural Networks, Sequential Models, Multivariate Time Series)

Member of technical leadership for model deployment for a very large user behavior model

Multiple papers on topics relevant to training models on graph and sequential data structures at KDD, ICML, NeurIPs, ICLR

Worked on scaling graph models to greater than 50m nodes Experience with large scale deep learning based recommender systems

Experience with production real-time and streaming environments

Contributions to common open source frameworks (pytorch-geometric, DGL)

Proposed new methods for inference or representation learning on graphs or sequences

Optimization (Training & Inference)

PhD focused on topics related to optimizing training of very large language models

5+ years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression

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

Data Preparation

Numerous Publications studying tokenization, data quality, dataset curation, or labeling

Leading contributions to one or more large open source corpus (1 Trillion + tokens)

Core contributor to open source libraries for data quality, dataset curation, or labeling

Benefits

Financial benefits

Inclusive benefits

Company

Capital One

Glassdoor

3.9

Capital One is a diversified banking company that offers early and later stage venture, and debt financing investments.

Founded in 1994

Mclean, Virginia, USA

10,001+ employees

http://www.capitalone.com

H1B Sponsorship

Capital One has a track record of offering H1B sponsorships. Please note that this does not guarantee sponsorship for this specific role. Below presents additional info for your reference. (Data Powered by US Department of Labor)

Distribution of Different Job Fields Receiving Sponsorship

Trends of Total Sponsorships

2023 (369)

2022 (881)

2021 (774)

2020 (816)