Software Engineer, Associate
Quick summary
- Work type
- On-site
- Location
- Dallas, TX
- Posted
- 1 day ago
- Nearby
- 99+ roles within 25 mi
Employer
About Goldman Sachs
Goldman Sachs is a leading global investment banking, securities, and investment management firm providing financial services to corporations, financial institutions, governments, and individuals.
Goldman Sachs currently has 187 open roles on FindRole.
Listed pay typically runs $130,000–$250,000 across 60 roles with salary data.
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At a glance
TL;DR · Software Engineer, Associate
As a GenAI Developer at Goldman Sachs' Wealth Management division, you will join a dynamic global team focused on advancing generative AI capabilities to support high-net-worth clients. Your primary responsibilities include collaborating with stakeholders to develop and implement AI solutions across various domains within wealth management, staying updated with the latest advancements in AI technologies, and conducting research to enhance existing AI capabilities. You will work closely with cross-functional teams to streamline business workflows and drive innovation on a global technology platform built on AWS Cloud. Required skills encompass expertise in Retrieval-Augmented Generation (RAG), vector stores, prompt engineering, large language model APIs, Python or Java programming, data analysis, problem-solving, and communication. Preferred competencies include experience with machine learning frameworks like TensorFlow or PyTorch, knowledge graphs, natural language processing, and computer vision technologies.
Skills
What you'll do
- Develop AI solutions for Wealth Management based on stakeholder requirements.
- Conduct research and experiments to enhance AI capabilities within the division.
- Stay current with advancements in AI and machine learning technologies.
- Design and optimize prompts for AI models to improve accuracy and relevance.
- Implement Retrieval-Augmented Generation (RAG) models to enhance tasks.
- Utilize vector stores for efficient data storage and retrieval processes.
What we're looking for
- Strong background in applied generative AI and experience with Retrieval-Augmented Generation (RAG) models.
- Proficiency in developing and implementing vector stores for efficient data storage and retrieval.
- Expertise in prompt engineering to optimize AI model performance.
- Knowledge of large language model APIs, including commercial and open-source options.
- Programming skills in Python or Java and strong analytical abilities with data analysis tools.
- Excellent problem-solving skills and attention to detail.
- Strong verbal and written communication skills for collaboration across teams.