Staff Applied Researcher

This is a fully remote position, open to applicants in California, +3 more states.

📋 Description

• Collaborate with data scientists, software engineers, machine learning engineers, and product managers to create AI-driven products.

• Utilize PyTorch, AWS Ultraclusters, Hugging Face, Lightning, and other relevant technologies to analyze extensive numeric and textual datasets.

• Develop AI foundation models through processes of design, training, evaluation, validation, and implementation.

• Perform applied research and translate emerging AI innovations into enhanced customer experiences.

• Convert intricate research findings into clear business objectives.

• Establish and guide innovative research paths that align with the organization’s long-term scientific goals.

• Influence strategic initiatives by collaborating with leaders in Applied Science, Engineering, and Product.

• Mentor and guide applied scientists and their managers without direct oversight responsibilities.

• Represent Capital One in the AI research community and engage with distinguished academic faculty.

⛳️ Requirements

• PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or similar fields with 4 years of Applied Research experience, OR M.S. in those fields with 6 years of Applied Research experience.

• Profound understanding of AI methodologies.

• Experience in developing large deep learning models for language, images, events, or graphs.

• Proficiency in one or more areas such as training optimization, self-supervised learning, robustness, explainability, or RLHF.

• Proven track record of deploying models at scale in terms of training data and inference volumes.

• Experience in delivering libraries, platform-level code, or solution-level code for existing products.

• A history of producing high-quality machine-learning concepts, including first-author publications or projects.

• Capability to independently manage and pursue a research agenda and execute long-term projects.

• Practical experience in developing AI foundation models utilizing open-source tools and cloud computing platforms.

• Preferred qualifications include proficiency in large language model training, publications, large-scale model deployment, GPU clusters, training optimization frameworks, graph and sequential models, recommender systems, real-time and streaming environments, open-source frameworks, data preparation, and multi-year AI/ML research projects.

🏝️ Benefits

• Performance-based incentive compensation, which may comprise cash bonuses and/or long-term incentives (LTI).

• Comprehensive, competitive, and inclusive health, financial, and additional benefits promoting total well-being.

• Employment authorization sponsorship may be offered for a new qualified applicant.

• Reasonable accommodations available for applicants who require them.