Compliance, New York, Vice President, AI/ML Engineer

About the role

We are seeking an experienced AI/ML Engineer to join our Compliance Engineering team. This role focuses on solving highly complex business problems using AI/ML techniques, incorporating the latest emerging trends in building vertical AI agents to run on data at massive scale.

Your Impact

• Design and architect scalable, reliable end-to-end AI/ML solutions tailored for compliance applications, ensuring adherence to regulatory requirements. This includes developing GenAI-driven solutions such as agentic frameworks for automating compliance processes, RAG pipelines, and embeddings for compliance knowledge bases.
• Explore diverse AI/ML problems, including model fine-tuning, prompt engineering, and experimentation with algorithmic approaches to address novel business challenges.
• Develop, test, and maintain high-quality, production-ready code.
• Lead technical projects from inception to completion, providing guidance and mentorship to junior engineers.
• Collaborate with compliance officers, legal counsel, and other stakeholders to translate business requirements into technical solutions.
• Participate in code reviews to ensure code quality, maintainability, and adherence to coding standards.
• Promote best practices for AI/ML development, including version control, testing, and documentation.
• Stay current with the latest advancements in AI/ML platforms, tools, and techniques.

Requirements

• Bachelor's, Master's, or PhD in Computer Science, Machine Learning, Mathematics, or a similar field.
• 7+ years of AI/ML industry experience for Bachelor’s/Master’s, or 4+ years for PhD, with a focus on Language Models.
• Strong foundation in machine learning algorithms, including deep learning architectures (e.g., transformers, RNNs, CNNs).
• Proficiency in Python and relevant libraries/frameworks such as TensorFlow, PyTorch, Hugging Face Transformers, and scikit-learn.
• Demonstrated expertise in GenAI techniques, including Retrieval-Augmented Generation (RAG), model fine-tuning, prompt engineering, AI agents, and evaluation techniques.
• Experience with embedding models and vector databases.
• Experience with MLOps practices, including model deployment, containerization (Docker, Kubernetes), CI/CD, and model monitoring.
• Strong verbal and written communication skills.
• Curiosity, ownership, and willingness to work in a collaborative environment.
• Proven ability to mentor and guide junior engineers.

Preferred Qualifications

• Experience with Agentic Frameworks (e.g., Langchain, AutoGen) and their application to real-world problems.
• Understanding of scalability and performance optimization techniques for real-time inference such as quantization, pruning, and knowledge distillation.
• Experience with model interpretability techniques.
• Prior experience in code reviews or architecture design for distributed systems.
• Experience with data governance and data quality principles.
• Familiarity with financial regulations and compliance requirements.

What We Offer

• Access to petabyte-scale structured and unstructured data to fuel AI/ML models, including textual data suitable for LLM applications.
• Opportunity to work with state-of-the-art LLM models and agentic frameworks.
• A collaborative environment where you can learn from and contribute to a team of experienced engineers and scientists.
• The chance to make a tangible impact on the firm's ability to manage risk and maintain its reputation.

About Compliance Engineering

We are a global team of engineers and scientists dedicated to preventing, detecting, and mitigating regulatory and reputational risks across Goldman Sachs. We build and operate a suite of platforms and applications that protect the firm and its clients.