Applied Researcher II

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Build AI foundation models for real customer impact by partnering with data scientists, software engineers, machine learning engineers, and product managers. Use a modern ML toolchain (PyTorch, Hugging Face, Lightning, VectorDBs, AWS Ultraclusters) to research, train, evaluate, validate, and implement large deep learning systems. Contribute high-impact applied research and translate complex work into tangible business goals for next-generation banking experiences.

Location: New York, Cambridge, San Francisco, San Jose

Workplace: Onsite

Employment Type: Full time

Job Function: Research & Scientific (R&D)

Key Responsibilities

•Partner with cross-functional teams to deliver AI-powered products that change how customers interact with their money.
•Leverage technologies including PyTorch, AWS Ultraclusters, Hugging Face, Lightning, and VectorDBs to extract insights from large volumes of numeric and textual data.
•Build AI foundation models across design, training, evaluation, validation, and implementation.
•Engage in high-impact applied research to transition the latest AI developments into next-generation customer experiences.
•Translate the complexity of your work into tangible business goals using interpersonal skills.

Pay and Benefits

Salary: USD 286,400 - 326,800 annually

Key Requirements

•Currently has, or is in the process of obtaining, a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields (with the stated exception timeline) or an M.S. plus required applied research experience.
•4+ years of Applied Research experience (as described for the M.S. pathway).
•Deep understanding of the foundations of AI methodologies.
•Hands-on experience building large deep learning models and expertise in one or more areas such as training optimization, self-supervised learning, robustness, explainability, or RLHF.
•A track record delivering models at scale for both training data and inference volumes.

Experience:Machine learningDeep learningNLPLLMsApplied researchOpen sourceGraph deep learning

Education:PhD / Doctorate in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields

Skills:LeadershipInterpersonal skillsCommunicationInnovationProblem-solving

Tech Stack:PyTorchAWS UltraclustersHugging FaceLightningVectorDBsPytorch-geometricDGLCloud computing

Company Brief

Discover Financial

Industry: Retail Banking

Website

Loading job details...

Preparing the role view and application actions.

Discover Financial

1 week ago

Applied Researcher II

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Location: New York, Cambridge, San Francisco, San Jose

Workplace: Onsite

Employment Type: Full time

Job Function: Research & Scientific (R&D)

Key Responsibilities

•Partner with cross-functional teams to deliver AI-powered products that change how customers interact with their money.
•Leverage technologies including PyTorch, AWS Ultraclusters, Hugging Face, Lightning, and VectorDBs to extract insights from large volumes of numeric and textual data.
•Build AI foundation models across design, training, evaluation, validation, and implementation.
•Engage in high-impact applied research to transition the latest AI developments into next-generation customer experiences.
•Translate the complexity of your work into tangible business goals using interpersonal skills.

Pay and Benefits

Salary: USD 286,400 - 326,800 annually

Key Requirements

•Currently has, or is in the process of obtaining, a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields (with the stated exception timeline) or an M.S. plus required applied research experience.
•4+ years of Applied Research experience (as described for the M.S. pathway).
•Deep understanding of the foundations of AI methodologies.
•Hands-on experience building large deep learning models and expertise in one or more areas such as training optimization, self-supervised learning, robustness, explainability, or RLHF.
•A track record delivering models at scale for both training data and inference volumes.

Experience:Machine learningDeep learningNLPLLMsApplied researchOpen sourceGraph deep learning

Education:PhD / Doctorate in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields

Skills:LeadershipInterpersonal skillsCommunicationInnovationProblem-solving

Tech Stack:PyTorchAWS UltraclustersHugging FaceLightningVectorDBsPytorch-geometricDGLCloud computing

Company Brief

Discover Financial

Industry: Retail Banking

Website