Applied Researcher 4 (AI Foundations, VLM Customization)
$219k - $250k • San Jose, CA • Full-time
Posted 1d ago
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Research Engineer
About the job
Capital One is seeking an Applied Researcher to join the AI Foundations team, focusing on Vision-Language Model (VLM) customization. This role involves partnering with cross-functional teams to deliver AI-powered products that enhance customer interactions with their money. You will leverage a broad stack of technologies, including Pytorch and Huggingface, to analyze large volumes of data and build AI foundation models through all phases of development. The position offers the opportunity to engage in high-impact applied research, translating complex AI developments into next-generation customer experiences and tangible business goals. The ideal candidate is innovative, creative, technically proficient, and possesses a deep understanding of AI methodologies, with a track record of delivering large deep learning models at scale.
Responsibilities
- Partner with data scientists, software engineers, ML engineers, and product managers to deliver AI-powered products.
- Leverage technologies like Pytorch, AWS Ultraclusters, Huggingface, and Lightning to analyze data.
- Build AI foundation models from design through training, evaluation, validation, and implementation.
- Conduct high-impact applied research to advance customer experiences.
- Translate complex work into tangible business goals.
- Collaborate with senior researchers on internal tech reports or conference submissions.
Requirements
- PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, or an M.S. with 2 years of applied research experience.
- Deep understanding of AI methodologies.
- Experience building large deep learning models (language, images, events, or graphs).
- Expertise in training optimization, self-supervised learning, robustness, explainability, or RLHF.
- Engineering mindset with a track record of delivering models at scale.
- Experience delivering libraries, platform code, or solution code to existing products.
- Track record of high-quality ideas or improvements in machine learning, demonstrated by publications or projects.
- Ability to own and pursue a research agenda autonomously.
- Comfort with open-source languages and developing AI foundation models using open-source tools and cloud platforms.
- Ability to reproduce and extend peer-reviewed AI research using modern open-source frameworks.
- Experience designing controlled experiments and documenting reproducibility results.
- PhD focus on NLP or Masters with 5 years of industrial NLP research experience.
- Experience with LLMs, fine-tuning, transfer learning, model adaptation, and model guidance.
- Experience deploying a fine-tuned large language model.
- Experience with data preparation, tokenization, data quality, dataset curation, or labeling.
- Contribution to a major open-source corpus or libraries for data quality/curation/labeling.