Vice President AI/ML Engineer

Goldman Sachs

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Quick summary

Work type: On-site
Location: New York, NY
Salary: $130,000–$250,000 / yr
Posted: 120 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $214k

This role $190k

$115k $268k

below market most similar roles pay here above market

This role pays more than 52% of similar roles. Most pay $174,600–$253,500 — the blue band above. At the midpoint, this role pays about $190k versus about $214k for comparable roles.

Based on 240 similar postings.

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 71 open roles on FindRole.

Listed pay typically runs $140,000–$250,000 across 34 roles with salary data.

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At a glance

TL;DR · Vice President AI/ML Engineer

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JOB TITLE: The Core Engineering, New York, Vice President, AI/ML Engineer The Core Engineering team seeks a Vice President, AI/ML Engineer to design and architect scalable, production-ready AI/ML solutions for compliance applications. You will build end-to-end systems including GenAI-driven solutions, agentic frameworks for automating processes, RAG pipelines, and embeddings for knowledge bases. Day-to-day responsibilities involve model fine-tuning, prompt engineering, and leading technical projects while mentoring junior engineers. You will utilize Python, TensorFlow, PyTorch, Hugging Face Transformers, and scikit-learn, alongside Docker, Kubernetes, and MLOps practices. The role addresses the business problem of mitigating regulatory and reputational risks by processing petabytes of structured and unstructured data. You will translate complex requirements from legal and compliance stakeholders into technical solutions, ensuring high-quality code and adherence to financial regulations within a centralized engineering framework.

Skills

Python PyTorch TensorFlow Hugging Face Transformers scikit-learn GenAI Large Language Models RAG Langchain AutoGen Docker Kubernetes CI/CD MLOps Vector Databases Transformers CNNs RNNs Quantization Knowledge Distillation Prompt Engineering

What you'll do

Design and architect scalable end-to-end AI/ML solutions specifically tailored for compliance applications.
Develop and implement GenAI-driven solutions including agentic frameworks, RAG pipelines, and embeddings.
Explore diverse AI/ML problems such as model fine-tuning, prompt engineering, and algorithmic experimentation.
Develop, test, and maintain high-quality, production-ready code for mission-critical business problems.
Lead technical projects from inception to completion while providing guidance and mentorship to junior engineers.
Translate business requirements from compliance and legal stakeholders into technical solutions.
Participate in code reviews to ensure quality, maintainability, and adherence to coding standards.
Stay current with the latest advancements in AI/ML platforms, tools, and techniques.

What we're looking for

A Bachelor's, Master's, or PhD degree in Computer Science, Machine Learning, Mathematics, or a similar field of study.
Preferably 7+ years of AI/ML industry experience for Bachelor’s/Masters, or 4+ years for PhD with a focus on Language Models (preferred).
Strong foundation in machine learning algorithms, including deep learning architectures like transformers, RNNs, and CNNs.
Proficiency in Python and libraries such as TensorFlow, PyTorch, Hugging Face Transformers, and scikit-learn.
Demonstrated expertise in GenAI techniques including RAG, model fine-tuning, prompt engineering, AI agents, and evaluation techniques.
Experience with embedding models, vector databases, and MLOps practices including Docker, Kubernetes, and CI/CD.
Proven ability to mentor junior engineers and strong verbal and written communication skills.
Experience with Agentic Frameworks, performance optimization, model interpretability, or financial regulations (preferred).