LLM Engineer, Investment Management Firm (Gurugram, India) (CLOSED)

We are seeking an LLM Engineer with strong expertise in natural language processing (NLP) and applied machine learning to join our technology and research team. The role focuses on leveraging large language models (LLMs) to drive insights from financial data, market information, and alternative datasets.

This is a unique opportunity to work at the intersection of AI, quantitative research, and investment strategy development, where advanced NLP techniques can directly influence decision-making in global markets.

Key Responsibilities:

• Develop, implement, and optimize large language models (LLMs) for applications such as sentiment analysis, news and market signal extraction, data enrichment, and predictive modeling.
• Collaborate with quant researchers and portfolio teams to design AI-driven tools that enhance investment research and trading workflows.
• Handle large-scale structured and unstructured financial datasets to create robust NLP pipelines.
• Continuously improve the performance, efficiency, and scalability of LLMs for real-time use cases.
• Stay ahead of developments in NLP, generative AI, and financial machine learning, ensuring that the team integrates cutting-edge techniques into applied research.
• Deploy ML models into production, integrating seamlessly with research and trading infrastructure.
• Identify and mitigate potential risks in AI models, including interpretability, robustness, and bias.

Key Requirements

• At least 2+ years of hands-on experience with LLMs, NLP, or deep learning in high-performance environments.
• Experience working with financial or quantitative datasets and deploying machine learning models into production.
• Solid understanding of NLP techniques such as transformers, tokenization, embeddings, and fine-tuning.
• Proficiency with ML frameworks (e.g., PyTorch, TensorFlow, HuggingFace, OpenAI APIs).
• Strong analytical and problem-solving skills with the ability to apply technical innovation to investment research or trading-related challenges.
• Exposure to algorithmic trading systems, portfolio research, or financial data modeling is a strong plus.

Interested parties please send your resume to Abhishrut Banerjee at .
Regrettably, only shortlisted candidates will be contacted.