The Core Engineering - Search & Entity Model Eng - Associate

Goldman Sachs; Bengaluru; On-site; INR 3,000,000 - 5,400,000; Full time

Job summary

Goldman Sachs is seeking an experienced AI/ML Engineer to join Compliance Engineering in Bengaluru. You will design GenAI-driven solutions, including agentic frameworks for automating compliance processes and RAG pipelines.

You will collaborate with compliance officers, legal counsel, and stakeholders to translate business requirements into scalable ML systems. You will develop production-grade code, stay current with AI/ML platforms, and apply best practices for deployment, monitoring, and

Qualifications

• Bachelor's, master's or PhD in Computer Science, Machine Learning, Mathematics, or a similar field.
• 3+ years AI/ML industry experience for Bachelor's/Masters; 1 year for PhD with focus on Language Models.
• Strong foundation in machine learning algorithms, incl. transformers, RNNs, CNNs.
• Proficiency in Python and libraries such as TensorFlow, PyTorch, Hugging Face Transformers, scikit-learn.
• GenAI techniques: RAG, fine-tuning, prompt engineering, AI agents, evaluation.
• Experience with embedding models and vector databases.
• MLOps: model deployment, Docker, Kubernetes, CI/CD, monitoring.
• Strong communication skills; curiosity and ownership.

Responsibilities

• Design, develop, and implement GenAI-driven solutions, incl. agentic frameworks for compliance automation and RAG pipelines.
• Explore diverse AI/ML problems and experiment with algorithms to address business challenges.
• Develop, test, and maintain production-grade code.
• Collaborate with compliance officers, legal counsel, and stakeholders to translate requirements into solutions.
• Participate in code reviews and promote best practices for AI/ML development.
• Stay current with AI/ML platforms, tools, and techniques.

Skills

Python

TensorFlow

PyTorch

Hugging Face

scikit-learn

GenAI

RAG

Embeddings

MLOps

Docker

Kubernetes

CI/CD

Model Deployment

Communication

Team Collaboration

Education

Bachelor's / Master's / PhD in CS/ML/Math

PhD: LM-focused research

Tools

LangChain

AutoGen

Vector Databases

Git

Job description

The Core Engineering builds and operates the platforms, applications, data solutions, models, and analytics that power critical processes for The Core divisions of the firm (e.g., Risk, responsible for the risk profile of firm activities; Controllers, responsible for the financial control and reporting obligations; Compliance, responsible for the firm's compliance, regulatory, and reputational risks; Corporate Treasury, responsible for the firm's liquidity, funding, balance sheet, etc.; and Human Capital Management, responsible for attracting, developing, and managing a global workforce). A centralized engineering structure in support of The Core enables a common platform model and operating framework that promotes consistent governance and scalable solutions, leveraging cloud, AI, and machine learning for innovation and efficiency. The Core Engineering's 2,000+ engineers and strats deliver engineering, data, analytics, and quantitative capabilities within six business units:

• Metrics & Analytics Platforms: responsible for the measurement and management of the firm's risk, capital, and liquidity for The Core functions
• The Core Strats: responsible for the development and implementation of models and other quantitative methodologies, including the accuracy and attribution of modeled metrics
• Financials & Reporting: responsible for facilitating the production of the firm's financials and a wide range of reporting functions
• Non-Financial Risk & Controls: responsible for non-financial risk and control processes
• Enterprise Platforms: responsible for platforms and applications that support critical operational processes across The Core such as payments, people processes, and procurement
• Shared Services: responsible for driving the adoption of consistent engineering strategy, including data platforms, cloud, and AI enablement, as well as the management of technology risk

Your Impact

Are you passionate about leveraging cutting-edge AI/ML techniques, including Large Language Models, to solve complex, mission-critical problems in a dynamic environment Do you want to contribute to safeguarding a leading global financial institution

Our Impact

We are Compliance Engineering, 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.

We offer:

• Access to petabyte scale of structured and unstructured data to fuel your AI/ML models, including textual data suitable for LLM applications.
• The opportunity to work with state-of-the-art LLM models and agentic framework.
• 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 firms ability to manage risk and maintain its reputation.

Within Compliance Engineering, we are seeking an experienced AI/ML Engineer to join our Engineering team. This role will focus on solving highly complex business problems using AI/ML techniques, incorporating latest emerging trends om building out vertical AI agents to run on data at massive scale.

How You Will Fulfill Your Potential

As a member of our team, you will:

• Design, develop, and implement GenAI-driven solutions, including agentic frameworks for automating compliance processes, RAG pipelines, and embeddings of compliance knowledge bases.
• Explore diverse AI/ML problems, such as model fine-tuning, prompt engineering, and experimentation with different algorithmic approaches to address novel business challenges.
• Develop, test, and maintain high-quality, production-ready code.
• Collaborate effectively with compliance officers, legal counsel, and other stakeholders to understand business requirements and translate them 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 to solve business problems.

Qualifications

A successful candidate will possess the following attributes:

• A Bachelors, master s or PhD degree in Computer Science, Machine Learning, Mathematics, or a similar field of study.
• Preferably 3+ years AI/ML industry experience for Bachelor s/Masters, 1 year 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, scikit-learn.
• Demonstrated expertise in GenAI techniques, including but not limited to Retrieval-Augmented Generation (RAG), model fine-tuning, prompt engineering, AI agents, and evaluation techniques.
• Experience working 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.

Experience in some of the following is desired and can set you apart from other candidates:

• 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/ architecture design for distributed systems.
• Experience with data governance and data quality principles.
• Familiarity with financial regulations and compliance requirements.