Senior AI ML Engineer - NLP/LLM Focused

Our client, a global leader in the financial sector is developing cutting-edge data and AI capabilities that drive growth for the company. As a Senior AI / ML engineer, this is an important, part of the team. This role is responsible for finding key data patterns and turning them into insights by using predictive modeling, data mining, ML algorithms, and models. You will be responsible for developing scalable solutions to provide data-driven insights.

The key to this role is someone that has created customized NLP solutions and not just using off the shelf products. Must also have Tree Models and Rag experience.

Key Responsibilities

• Design, develop, and deploy solutions with best practices in statistics, ML, deep learning, and models. Experience in areas like classification models, forecasting, uplift modeling, foundational model fine-tuning, etc. help.
• Identify growth opportunities in underwriting and risk assessment through AI/ML.
• Collaborate cross-functionally to drive scalability and impact of the solutions.
• Communicate complex concepts and findings to leadership in a clear manner.
• Stay up-to-date with the latest advancements in AI.

Required Professional and Technical Expertise:

• Solid Tree Models and Rag experience
• Master's degree in Statistics, Data Science, Mathematics, Computer Science, Operational Research, or related disciplines.
• 5+ years' experience with data science/machine learning techniques (logistic regression, hierarchical regression, neural networks, etc.).
• NLP and natural language understanding expertise.
• 2+ years of experience working with NLP and LLM.
• Expertise in Python, SQL and with data science and data analytics packages.
• Experience with developing and industrializing scalable AI solutions from conception to delivery.
• Expertise working in cloud services using big data solutions.
• Proven ability to understand, cleanse, and integrate massive data sets and demonstrate knowledge with data modeling workflow.
• Strong communication skills.

Preferred:

• Masters in Statistics, Data Science, Mathematics, Computer Science, Operational Research, or related areas.
• Experience in risk industry such as insurance, handling underwriting, claims, or risk management.
• Knowledge of actuarial science.