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Applied Researcher II (AI Foundations, LLM Core and Agentic AI)

SpringCube

Full-time - Senior Engineer

Banking & Financial Services

United States, San Francisco - California

Published 3 weeks ago

Salary: Disclosed upon interview

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Job Description

The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.

Company Overview
A leading financial services organization is advancing trustworthy and scalable AI systems to transform the banking experience. The company leverages machine learning and AI to deliver real-time, intelligent, and automated customer solutions while maintaining high standards of reliability and ethics. Its applied science and engineering teams focus on research-driven innovation, scalable AI infrastructure, and next-generation product experiences that reshape customer interactions.

Summary
The Applied Researcher II will contribute to the development of AI foundation models and large language models (LLMs), enabling innovative AI-driven products across the organization. The role involves research, model design, training, evaluation, and deployment of AI solutions, bridging cutting-edge AI advancements with real-world applications.

Responsibilities

  • Partner with cross-functional teams of data scientists, software engineers, machine learning engineers, and product managers to deliver AI-powered products.
  • Leverage technologies including PyTorch, AWS Ultraclusters, Huggingface, Lightning, and VectorDBs to analyze large volumes of numeric and textual data.
  • Build AI foundation models through all phases: design, training, evaluation, validation, and implementation.
  • Conduct applied research to translate emerging AI developments into practical solutions.
  • Communicate complex technical findings in clear, actionable terms to business stakeholders.
  • Propose and implement novel methods for inference, representation learning, and optimization of large-scale models.
  • Contribute to open-source frameworks and publications, advancing the broader AI research community.

Qualifications

Basic Qualifications

  • PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, or in process of obtaining one by start date, with 2 years of applied research experience; or
  • Master’s in related field with 4 years of applied research experience.

Preferred Qualifications

  • PhD in Machine Learning, Computer Science, Applied Mathematics, Electrical Engineering, or related fields.
  • Specialization in NLP, LLM pre-training, geometric deep learning, optimization of large-scale models, or fine-tuning techniques.
  • Experience building large-scale deep learning models (10B+ parameters, 500B+ tokens) and deploying in real-time or streaming production environments.
  • Multiple publications in top-tier AI conferences (ACL, NAACL, EMNLP, NeurIPS, ICML, ICLR).
  • Contributions to open-source AI frameworks (e.g., PyTorch-Geometric, DGL).
  • Proven ability to define and execute impactful research agendas independently.
  • Strong engineering mindset with hands-on experience in scalable model training, inference optimization, and deployment.
  • Expertise in transfer learning, model guidance, instruction tuning, or dialogue fine-tuning for LLMs.

Disclaimer
SpringCube curates tech job listings from various company websites to support tech professionals in globally.

1. No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
2. No Client Relationship: This company is not a client of SpringCube unless stated.
3. To Apply: Click the “Apply” button to be redirected to the hiring company’s application page for this job.
4. No Liability: SpringCube is not liable for inaccuracies.

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