AI / ML Engineer

A Leading Global Consultancy is seeking a highly skilled AI / ML Engineer to join its financial risk advisory practice in Mumbai. In this advanced technological role, you will design, validate, and deploy intelligent pipelines that power financial analytics frameworks. Furthermore, you will build Retrieval-Augmented Generation (RAG) models to optimize model risk governance workflows. Consequently, this position is vital for driving digital transformation across matrixed global quantitative environments.

The AI / ML Engineer must demonstrate expert programming capabilities in Python infrastructure development. Additionally, you will manage CI/CD pipelines to ensure continuous integration of automated data tools from staging down to cloud deployment. Therefore, the company is looking for a computer science engineer with a passion for distributed machine learning engines. If you want to engineer cutting-edge AI architectures for financial leaders, this AI / ML Engineer role provides an elite path.

Key Responsibilities

• Build and deploy scalable LLM pipelines, RAG-based agentic architectures, and predictive ML models.
• Develop robust Python infrastructure code to automate quantitative model tooling and risk engines.
• Design, manage, and monitor MLOps CI/CD pipelines for reliable model delivery across platforms.
• Configure vector stores and semantic search registries to index complex risk-relevant documentation.
• Deploy containerized microservices on cloud architectures using Docker and FastAPI frameworks.
• Collaborate with quantitative developers and model validators to translate business gaps into AI solutions.
• Optimize model latency and compute performance using parallel computing libraries.
• Enforce strict code quality metrics, comprehensive automated unit testing, and git repository hygiene.
• Analyze unstructured financial text logs to extract critical regulatory data indicators.
• Provide expert technical consulting support to global multidisciplinary model governance teams.

Requirements and Qualifications

• B.Tech / B.E. / M.Tech in Computer Science, Software Engineering, or quantitative sciences.
• 1 to 4 years of hands-on experience as an AI/ML Engineer or Core Data Scientist.
• Expert programming in Python, using LangChain, LlamaIndex, Scikit-learn, Pandas, and PySpark.
• Familiarity with vector databases (Pinecone, ChromaDB, or FAISS) and SQL data tools.
• Basic knowledge of financial risk domains or model validation frameworks is a major plus.