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Capital Group · 5 months ago

Applied Scientist III

Los Angeles

Full-time

Onsite

Senior Level, Lead/Staff

$201K/yr - $342K/yr

10+ years exp

Capital Group is a leading asset management company seeking an Applied Scientist III to shape the future of AI and establish the GenAI strategy for the Client Group. The role involves researching and developing scalable applications using cutting-edge technology, mentoring a team, and providing thought leadership to transform business visions into AI applications.

Financial Services

Comp. & Benefits

Responsibilities

Play a pivotal role in shaping the future of AI at Capital Group and help to establish the GenAI strategy for the Client Group

Research and develop scalable applications using Large Language Models (LLMs) and Agentic AI, such as conversational assistants to retrieve information about mutual fund products or market insights and guide clients through investment decisions

Provide thought leadership in discussions with product and technical leaders to transform business and product visions into groundbreaking AI applications

Analyze behavioral data, market news, and economic trends to personalize investment outcomes, and develop AI tools that help sales, marketing, and service teams offer relevant solutions to financial advisors

Design and review AI solutions with a focus on excellence, scalability, employing best practices for data management, model development, and evaluation to ensure the highest quality outcomes

Independently drive AI research and innovation with high conviction, collaborating with other scientists and engineers to develop and publish new industry leading ideas, and mentor a talented team of both junior and senior applied scientists

Qualification

Deep Neural NetworksGenerative AILarge Language ModelsMachine LearningDeep Learning architecturesAdvanced prompt engineeringAI researchInnovationThought leadershipTeam collaborationMentoring

Required

MS in (PhD preferred) Computer Science, Artificial Intelligence, Machine Learning, or related technical field

10+ years (post MS)/ 8+ years (post PhD) of relevant work experience, including industry experience or as a Researcher in a lab

Practical experience with the latest advancements in Large Language Models (LLM) and generative AI technology including RAG, including parameter-efficient fine-tuning, instruction fine-tuning, advanced prompt engineering, and Agentic AI frameworks

Deep technical knowledge of Machine Learning and Deep Learning architectures, such as Transformers, training methodologies, and optimization techniques

A strong commitment to staying current with the latest advancements in the field, applying cutting-edge academic research to solve complex business challenges, and successfully bringing innovative solutions into production

Experience working effectively with software engineering teams

Experience contributing to research communities- publishing papers/blog articles related to machine learning is a plus