Senior Machine Learning Engineer

James Search Group; New York (NY); On-site; USD 180,000 - 250,000; Full time

Benefits offered by this job

Bonus

Pension

401(k)

Comprehensive benefits

Job summary

James Search Group is partnering with a leading global property and casualty insurer to recruit a Senior AI/ML Engineer for a high‑impact enterprise data and AI team. You will design and deploy scalable AI/ML models addressing underwriting, claims, risk analytics, and customer experience.

This hands‑on role emphasizes translating complex AI outputs into actionable business recommendations for non‑technical stakeholders and delivering real‑world impact through advanced data strategies.

Qualifications

• Master's degree required in a quantitative field.
• Minimum 5 years of hands-on data science and ML experience.
• 2+ years working with large language models and foundational AI systems.
• Proficient in Python and SQL with data science libraries.

Responsibilities

• Develop and deploy end-to-end AI/ML models for business use cases.
• Identify AI opportunities across underwriting, claims, risk analytics, and customer experience.
• Collaborate with technical and business stakeholders to deliver actionable insights.
• Translate complex AI outputs into clear business recommendations for non-technical stakeholders.
• Stay current with AI/ML trends and integrate new tools and methods.

Skills

Python

SQL

ML/AI

LLMs

Cloud (Azure/AWS)

Data modeling

NLP/NLU

Education

Master's degree

Tools

Azure

AWS

Job description

Compensation: $180,000 - $250,000 base + bonus + comprehensive benefits (including pension, 401(k), and more)

About the role and client

James Search Group is excited to partner with a leading global property and casualty insurance carrier to identify a Senior AI/ML Engineer to join a high-impact enterprise data and artificial intelligence team. This group is at the forefront of transforming how the insurance industry leverages data, analytics, and emerging AI technologies to enhance decision-making and drive profitability across the organization.

As a key contributor, you will design and implement scalable machine learning and AI-driven solutions to solve complex business challenges. This role is ideal for a hands-on, innovative professional passionate about delivering real-world business impact through advanced data modeling and machine learning strategies.

Key Responsibilities:

• Develop and deploy end-to-end AI/ML models—including classification, forecasting, uplift modeling, and fine-tuning of foundational models.
• Identify use cases for AI across areas such as underwriting, claims, risk evaluation, and customer experience.
• Work cross-functionally with technical and business stakeholders to deliver actionable insights and scalable solutions.
• Translate sophisticated AI/ML outputs into clear business recommendations for non-technical stakeholders.
• Stay current with the latest trends in AI/ML, incorporating new tools and methodologies to enhance the organization’s data capabilities.

Required Qualifications:

• Master’s degree in Computer Science, Data Science, Mathematics, Statistics, Operations Research, or a related field.
• Minimum of 5 years of hands-on experience in data science and machine learning, including techniques like regression, decision trees, neural networks, and ensemble models.
• At least 2 years of experience working with large language models (LLMs) and foundational AI systems.
• Strong programming skills in Python and SQL, with experience using popular data science libraries and frameworks.
• Background in building and deploying ML models in cloud environments (e.g., Azure, AWS).
• Proficient in handling and integrating large structured and unstructured datasets.
• Strong analytical skills with a demonstrated ability to extract actionable insights from complex data.
• Excellent verbal and written communication skills; capable of simplifying complex technical concepts for business audiences.

Preferred Qualifications:

• Expertise in natural language processing (NLP) and natural language understanding (NLU).
• Experience leading multi-functional AI projects or initiatives.
• Background in insurance, particularly within claims, underwriting, or risk analytics.
• Familiarity with actuarial data, insurance KPIs, or related industry-specific datasets.
• Collaborative mindset with the ability to drive change and build consensus.