Staff ML Engineer – LLM/RAG

Our client is a pioneering fintech platform transforming the wealth management sector through AI-powered personalization. With a commitment to offering customized wealth solutions that align with everyone’s unique objectives, they are spearheading a paradigm shift in personalized wealth management.

They are hiring a Staff ML Engineer to play a key role in their game-changing investment platform. The successful candidate will be responsible for crafting, refining, and implementing state-of-the-art Large Language models (LLMs) and advanced Retrieval Augmented Generation (RAG) pipelines to transform investment intelligence.

Responsibilities:

• As the Staff ML Engineer, you will develop and refine Large Language Models (LLMs) for diverse tasks like question answering, summarization, and reasoning.

• You will construct sophisticated Retrieval Augmented Generation (RAG) pipelines, integrating methods like rewriting, embedding fine-tuning and hybrid search.

• Establish thorough evaluation frameworks and metrics to gauge model performance effectively.

• Deploy models into production environments, prioritizing low latency, reliability and scalability.

• Engage in close collaboration with product and engineering teams to create comprehensive end-to-end product systems.

Skillset:

• PhD, Master’s, or Bachelor’s degree in computer science, mathematics, engineering or similar.

• Experience in NLP/LLM with a solid understanding of cutting-edge research.

• Expertise in LLM fine-tuning techniques and inference frameworks.

• Proficient in machine learning/deep learning frameworks such as TensorFlow, PyTorch, etc.

• Exhibit strong programming proficiency in Python and SQL.

• Possess an analytical mindset with exceptional problem-solving skills.

Salary: $220k-$240k

If this sounds like the role for you, apply now in the link below or email your CV directly to angelo@alldus.com for consideration.

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