LLM Engineer - Investment Management Firm

Amethyst Partners, a distinguished investment management firm in Gurugram, India, is actively seeking a skilled LLM Engineer to join our dynamic technology and research team. This pivotal role requires deep expertise in Natural Language Processing (NLP) and applied machine learning, with a specific focus on harnessing the power of Large Language Models (LLMs). You will be instrumental in extracting valuable insights from diverse financial data, market intelligence, and alternative datasets.

This is a unique and exciting opportunity to operate at the confluence of Artificial Intelligence, quantitative research, and sophisticated investment strategy development. Your work will directly contribute to shaping decision-making in the fast-paced global markets through the application of advanced NLP techniques.

Key Responsibilities:

• Develop, implement, and meticulously optimize Large Language Models (LLMs) for a variety of critical applications including sentiment analysis, extraction of news and market signals, data enrichment, and predictive modeling.
• Collaborate closely with our quantitative researchers and portfolio management teams to conceptualize and build AI-driven tools that significantly enhance investment research processes and trading workflows.
• Efficiently manage and process large-scale structured and unstructured financial datasets to construct robust and scalable NLP pipelines.
• Continuously strive to enhance the performance, efficiency, and scalability of our LLMs, ensuring their suitability for real-time applications.
• Maintain a forward-thinking approach by staying abreast of the latest advancements in NLP, generative AI, and financial machine learning, ensuring the integration of cutting-edge techniques into our applied research efforts.
• Successfully deploy machine learning models into production environments, ensuring seamless integration with our existing research and trading infrastructure.
• Proactively identify and implement strategies to mitigate potential risks associated with AI models, including interpretability, robustness, and bias.

Key Requirements:

• A minimum of 2 years of hands-on experience with LLMs, NLP, or deep learning, preferably in high-performance computing environments.
• Demonstrated experience working with financial or quantitative datasets and a proven track record of deploying machine learning models into production settings.
• A solid foundational understanding of core NLP techniques such as transformers, tokenization, embeddings, and model fine-tuning.
• Proficiency with major machine learning frameworks and tools, including but not limited to PyTorch, TensorFlow, HuggingFace, and OpenAI APIs.
• Exceptional analytical and problem-solving capabilities, with a demonstrated ability to apply technical innovation to address investment research or trading-related challenges.
• Prior exposure to algorithmic trading systems, portfolio research, or financial data modeling is considered a significant advantage.