Goldman Sachs
AI Acceleration Engineer, Engineering, Associate, Dallas
Goldman Sachs, Dallas, Texas, United States, 75215
Overview
AI Acceleration Engineer, Engineering, Associate, Dallas — Goldman Sachs. This role is part of the agile AI Innovation Acceleration team, focused on rapidly prototyping and building cutting-edge AI use cases that address critical business needs. The team demonstrates the transformative potential of AI, delivers impactful solutions, and transfers code, knowledge, and ownership to the respective business and engineering teams. This hands-on engineering role shapes the future of AI adoption at Goldman Sachs and fosters a culture of innovation and accelerated development. Responsibilities
Rapid Prototyping & End-to-End Development: Lead the end-to-end development of AI/ML models and applications, from ideation and data exploration to rapid prototyping and initial deployment. Business Partnership & Solution Architecture: Collaborate with business and engineering teams to understand challenges and customer needs, identify high-impact AI use cases, and translate requirements into robust technical specifications and solution architectures. Solution Implementation & Delivery: Architect, implement, and deliver scalable, robust, and maintainable AI solutions that integrate with existing systems and workflows within the Goldman Sachs ecosystem. Knowledge Transfer & Enablement: Provide comprehensive documentation, training, mentorship, and hands-on enablement to ensure receiving teams can continue development of AI solutions. Technology & Innovation Leadership: Stay current with AI and ML advancements, evaluating and recommending tools, techniques, and best practices to drive innovation. Qualifications
Bachelor's or Master's degree in Computer Science, Data Science, or a related quantitative field. 5+ years of hands-on experience in AI/ML development with a proven track record of delivering end-to-end AI solutions. Experience building and deploying end-to-end AI applications, particularly those leveraging LLMs and related frameworks (prompt engineering, fine-tuning, Retrieval Augmented Generation (RAG), and agentic frameworks). Strong proficiency in Python and AI/ML frameworks (TensorFlow, PyTorch). Ability to translate complex business requirements into technical architectures and implement robust systems. Experience with cloud platforms (AWS, Azure, GCP) and MLOps practices for model deployment and management. Excellent communication skills to articulate complex concepts to technical and non-technical stakeholders; strong collaboration and mentoring abilities; willingness to lead or contribute to cross-functional projects. Job Details
Seniority level: Not Applicable Employment type: Full-time Job function: Engineering and Information Technology
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AI Acceleration Engineer, Engineering, Associate, Dallas — Goldman Sachs. This role is part of the agile AI Innovation Acceleration team, focused on rapidly prototyping and building cutting-edge AI use cases that address critical business needs. The team demonstrates the transformative potential of AI, delivers impactful solutions, and transfers code, knowledge, and ownership to the respective business and engineering teams. This hands-on engineering role shapes the future of AI adoption at Goldman Sachs and fosters a culture of innovation and accelerated development. Responsibilities
Rapid Prototyping & End-to-End Development: Lead the end-to-end development of AI/ML models and applications, from ideation and data exploration to rapid prototyping and initial deployment. Business Partnership & Solution Architecture: Collaborate with business and engineering teams to understand challenges and customer needs, identify high-impact AI use cases, and translate requirements into robust technical specifications and solution architectures. Solution Implementation & Delivery: Architect, implement, and deliver scalable, robust, and maintainable AI solutions that integrate with existing systems and workflows within the Goldman Sachs ecosystem. Knowledge Transfer & Enablement: Provide comprehensive documentation, training, mentorship, and hands-on enablement to ensure receiving teams can continue development of AI solutions. Technology & Innovation Leadership: Stay current with AI and ML advancements, evaluating and recommending tools, techniques, and best practices to drive innovation. Qualifications
Bachelor's or Master's degree in Computer Science, Data Science, or a related quantitative field. 5+ years of hands-on experience in AI/ML development with a proven track record of delivering end-to-end AI solutions. Experience building and deploying end-to-end AI applications, particularly those leveraging LLMs and related frameworks (prompt engineering, fine-tuning, Retrieval Augmented Generation (RAG), and agentic frameworks). Strong proficiency in Python and AI/ML frameworks (TensorFlow, PyTorch). Ability to translate complex business requirements into technical architectures and implement robust systems. Experience with cloud platforms (AWS, Azure, GCP) and MLOps practices for model deployment and management. Excellent communication skills to articulate complex concepts to technical and non-technical stakeholders; strong collaboration and mentoring abilities; willingness to lead or contribute to cross-functional projects. Job Details
Seniority level: Not Applicable Employment type: Full-time Job function: Engineering and Information Technology
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