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Duck Creek Technologies

Policy administration, billing, claims, rating software

Director, Applied AI and Machine Learning

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeCalifornia, USA$187.5k - $333.9k

About the Job

Requirements

  • At least 10 years of experience in machine learning, data science, AI engineering, or a related technical discipline, including meaningful hands-on model development and improvement.
  • At least 5 years leading technical teams, including data scientists and teams responsible for ML platforms, model operations, or production ML systems.
  • Direct experience with model training and refinement, model selection, and fine-tuning or other adaptation techniques for product requirements.
  • Experience delivering machine learning or AI capabilities into production, with accountability for model quality, reliability, monitoring, iteration, and business impact.
  • Experience designing or leading model evaluation approaches that measure quality against representative tasks and inform model, prompt, routing, or product decisions.
  • Experience partnering with Product and Engineering teams to define use cases, build technical foundations, and ship customer- or team-used capabilities.
  • Experience with external AI, cloud, or data vendors, including evaluating technical fit and leading partnership or commercial discussions with procurement, legal, and executive partners.
  • A bachelor's degree in computer science, data science, engineering, mathematics, or a related field, or equivalent practical experience.
  • Candidates must be legally authorized to work in the country of the job location; the company does not sponsor visa petitions.
  • Candidates should be within a reasonable distance of designated locations and open to participating in team-directed in-person collaboration.
  • Travel up to 25% may be required.

Responsibilities

  • Set AI and machine learning strategy for Duck Creek Intelligence, aligning model and platform investments with product priorities, customer needs, and business outcomes.
  • Lead the model lifecycle from problem framing and data readiness through model selection, training, refinement, fine-tuning, evaluation, deployment, monitoring, and ongoing improvement.
  • Guide teams in selecting approaches for use cases, including foundation models, task-specific models, traditional machine learning, and hybrid methods; establish when to use, adapt, replace, or retire models.
  • Build shared model access and routing capabilities, including selection criteria, orchestration patterns, fallback behavior, versioning, and operational controls across internal and external models.
  • Establish an AI evaluation practice combining offline benchmarks, task-specific quality measures, expert review, safety and reliability checks, and production feedback, and use its results to inform Product and Engineering decisions.
  • Build and operate MLOps and model platform capabilities for reproducible training, deployment, observability, performance and cost management, and safe production iteration.
  • Lead, coach, and grow data scientists and ML operations and engineering teams; set goals, develop technical leaders, and enable collaboration across disciplines.
  • Partner with Product, Engineering, architecture, security, legal, and insurance subject matter experts to turn workflows and domain knowledge into well-scoped, measurable AI solutions.
  • Represent Duck Creek in strategic model and technology partnerships; evaluate providers and lead technical and commercial discussions, including partnership and model-development negotiations with major vendors such as Google, in coordination with internal stakeholders.
  • Set standards for data quality, model documentation, privacy, security, responsible AI, governance, and human oversight throughout the model lifecycle.
  • Communicate technical trade-offs to executives and cross-functional teams to align on priorities, risks, investment decisions, and success measures.

Desired Qualifications

  • A graduate degree in a relevant technical field.
  • Experience with large language models, retrieval-augmented generation, agentic workflows, or other generative AI patterns, and sound judgment about when simpler methods are more appropriate.
  • Experience building model gateways, routing and orchestration systems, evaluation platforms, feature or data pipelines, and cloud-native ML infrastructure.
  • Experience in SaaS, enterprise software, insurance, or another domain with complex workflows, sensitive data, and high reliability standards.
  • Knowledge of responsible AI practices, security and privacy controls, model risk management, and human-in-the-loop review.

About the Company

Duck Creek Technologies

Policy administration, billing, claims, rating software

Duck Creek Technologies provides software for property and casualty insurance carriers, including policy administration, billing, claims management, and a flexible rating engine. It operates on a subscription-based model, earning revenue from software licensing, implementation services, and ongoing support. The platform is designed for speed and scalability, allowing insurers to adapt quickly to market changes, develop new products, and improve service delivery across personal, commercial, and specialty lines. Compared to competitors, Duck Creek offers a comprehensive, industry-focused suite that covers core insurance operations with a modular, scalable architecture, helping a broad range of insurers streamline operations and enhance customer experiences. The company aims to enable insurers to meet current demands and support future growth.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Boston, MA
Founded
2000

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