LLM Engineer

Amethyst Partners is seeking a skilled LLM Engineer to join its dynamic technology and research team in Gurugram. This role is ideal for professionals with a strong background in natural language processing (NLP) and applied machine learning, eager to leverage the power of large language models (LLMs) for financial data analysis.

This is a unique opportunity to work at the forefront of AI, quantitative research, and investment strategy development. You will utilize advanced NLP techniques to directly influence decision-making in global financial markets.

Key Responsibilities:

• Develop, implement, and optimize large language models (LLMs) for critical applications including sentiment analysis, news and market signal extraction, data enrichment, and predictive modeling.
• Collaborate closely with quantitative researchers and portfolio teams to design innovative AI-driven tools that enhance investment research and trading workflows.
• Manage and process large-scale structured and unstructured financial datasets to build robust NLP pipelines.
• Continuously enhance the performance, efficiency, and scalability of LLMs for real-time operational use cases.
• Stay abreast of the latest advancements in NLP, generative AI, and financial machine learning, ensuring the integration of cutting-edge techniques into applied research.
• Deploy machine learning models into production environments, ensuring seamless integration with existing research and trading infrastructure.
• Identify and implement strategies to mitigate potential risks associated with AI models, focusing on interpretability, robustness, and bias.

Key Requirements:

• A minimum of 2 years of hands-on experience with LLMs, NLP, or deep learning in high-performance computing environments.
• Proven experience working with financial or quantitative datasets and deploying machine learning models into production.
• A solid understanding of core NLP techniques such as transformers, tokenization, embeddings, and fine-tuning.
• Proficiency in machine learning frameworks including PyTorch, TensorFlow, HuggingFace, and OpenAI APIs.
• Exceptional analytical and problem-solving skills, with a demonstrated ability to apply technical innovation to investment research or trading challenges.
• Exposure to algorithmic trading systems, portfolio research, or financial data modeling is considered a significant advantage.