Applied Researcher I (AI Foundations, LLM Customization, Finetuning, Reinforcement Learning)
About the role
The AI Foundations team at Capital One is central to bringing our vision for AI to life. We work across the entire research lifecycle, from academic partnerships to production systems. We collaborate with product, technology, and business leaders to apply the latest in AI to our business needs.
Responsibilities
- Partner with a cross-functional team to deliver AI-powered products that enhance customer interactions.
- Leverage a diverse stack of technologies including PyTorch, AWS UltraClusters, Huggingface, Lightning, and Vector Databases to uncover insights from vast datasets.
- Build AI foundation models throughout the development lifecycle, from design to deployment.
- Engage in high-impact applied research to advance AI capabilities and customer experiences.
- Communicate complex AI concepts to stakeholders to align on business goals.
Requirements
- Currently pursuing or recently obtained a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields.
- Experience with open-source tools and cloud computing platforms.
- Knowledge of AI methodologies, including training optimization, self-supervised learning, robustness, explainability, and RLHF.
- Experience with large-scale deep learning models and one or more of the following areas: language, images, events, or graphs.
- Track record of delivering models at scale in terms of training data and inference volumes.
- Experience in developing libraries, platform-level code, or solution-level code for existing products.
- Publications in deep learning theory and applications, including ACL, NAACL, EMNLP, NeurIPS, ICML, ICLR, and others.
- Experience with large language model training and fine-tuning, including contributions to major open-source corpora and libraries.
- Knowledge of transfer learning, model adaptation, and guidance techniques.
- Experience with data preparation, tokenization, and dataset curation.
Qualifications
- Master's degree in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with a PhD to be obtained by the start date.
- At least 2 years of relevant industrial experience in applied research.
- Preferred qualifications include a PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering, or related fields.
- Experience with NLP and publications in ACL, NAACL, EMNLP, NeurIPS, ICML, ICLR, and similar conferences.
- Experience with large language model training and fine-tuning, including contributions to major open-source corpora and libraries.
- Experience with transfer learning, model adaptation, and guidance techniques.
- Experience with data preparation, tokenization, and dataset curation.
Skills
- Strong programming skills in Python, R, or equivalent.
- Experience with deep learning frameworks like PyTorch, TensorFlow, or Huggingface.
- Understanding of natural language processing (NLP).
- Experience with large-scale data processing and analysis.
- Ability to communicate complex technical concepts to non-technical stakeholders.
Benefits
Capital One offers a comprehensive benefits package, including health, financial, and wellness programs designed to support your total well-being. Learn more at the Capital One Careers website.
Pay
Salaries for this role vary by location and can range from $218,700 - $272,300 annually, depending on experience and qualifications. For more details, refer to the provided salary ranges.
Schedule
This role is full-time and requires regular attendance and availability to meet the demands of the position.
Benefits
Capital One provides a wide range of benefits, including:
- Health, dental, and vision insurance
- Retirement savings plans
- Flexible spending accounts
- Employee assistance programs
- Wellness programs
- Professional development opportunities
Company Information
Capital One is an equal opportunity employer committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. For more information, visit the Capital One Careers website.