Senior AI/ML Engineer

A global organization operating in the financial and risk services sector is building out its Enterprise Data & Artificial Intelligence function to transform how data and advanced analytics drive business performance.

The Data & AI team develops enterprise-scale capabilities that enhance decision-making, improve operational efficiency, and unlock growth opportunities across the organization. This team partners closely with business and technology stakeholders to deploy innovative AI solutions that deliver measurable impact.

We are seeking a Senior AI/ML Engineer to help design, build, and scale advanced analytics and machine learning solutions that support strategic business objectives.

Role Overview

The Senior AI/ML Engineer will play a critical role in identifying meaningful patterns in complex data and translating them into scalable, production-ready AI solutions. This individual will leverage predictive modeling, machine learning, deep learning, and large language models to drive operational improvements and financial performance.

This role requires strong technical depth, business acumen, and the ability to operate in a fast-paced, cross-functional environment. The ideal candidate is passionate about emerging AI technologies and thrives on solving complex, ambiguous problems.

Key Responsibilities

• Design, develop, and deploy AI/ML solutions using best practices in statistics, machine learning, deep learning, and foundational models
• Build and evaluate models such as classification, forecasting, propensity modeling, uplift modeling, and LLM fine-tuning
• Identify growth and optimization opportunities across operational workflows and customer-facing processes through AI augmentation
• Collaborate cross-functionally with business, technology, and transformation teams to ensure scalable implementation
• Communicate technical concepts and analytical findings clearly to non-technical stakeholders
• Research and apply emerging AI/ML advancements to continuously improve enterprise capabilities
• Develop scalable solutions from ideation through production deployment
  
  
  

Required Qualifications

• Master’s degree in Statistics, Data Science, Mathematics, Computer Science, Operations Research, or a related field
• 5 years of hands-on experience applying machine learning techniques (e.g., regression models, decision trees, random forests, neural networks, etc.)
• 2 years of experience working with large language models
• Strong proficiency in Python and SQL
• Experience working with both structured and unstructured data
• Demonstrated experience building and deploying scalable AI solutions in cloud environments (e.g., Azure, AWS, or similar platforms)
• Experience working with large, complex, and disparate datasets
• Strong analytical rigor and ability to derive actionable insights from ambiguous information
• Excellent communication skills with the ability to translate complex analysis into business recommendations
  
  
  

Preferred Qualifications

• Ph.D. in a quantitative discipline
• Experience with natural language processing and natural language understanding
• Experience leading projects or initiatives across business units
• Ability to influence stakeholders and drive change
• Experience within regulated or risk-based industries
• Familiarity with domain-specific data sets related to underwriting, claims, risk assessment, or actuarial functions
  
  
  

Compensation: $180,000 to $200,000 annually Compensation is based on a range of factors that include relevant experience, knowledge, skills, other job-related qualifications.