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Company

Original Job Post

Capital One · 4 days ago

Applied Researcher I

San Francisco, CA

Full-time

Onsite

Mid Level

$230K/yr - $262K/yr

2+ years exp

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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 to deliver AI-powered products.

Leverage a broad stack of technologies to reveal insights within data.

Build AI foundation models through all phases of development.

Engage in high impact applied research to enhance customer experiences.

Translate complex 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.

Open-source languagesAI methodologiesDeep learning modelsTraining optimizationSelf-supervised learningRobustnessExplainabilityRLHFDelivering models at scaleDelivering librariesResearch agendaDeep LearningModel SparsificationQuantizationTraining ParallelismGradient CheckpointingModel CompressionCompiler DesignTransfer LearningModel AdaptationModel GuidanceFine-tuningTokenizationData QualityDataset CurationOpen Source Contribution

Required

PhD or M.S. with at least 2 years of experience in Applied Research

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.

Preferred

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

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

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

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

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

Contribution to a major open source corpus

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

Benefits

Performance based incentive compensation

Health benefits

Financial 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

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2020 (816)