Applied AI Engineer

4 days ago

Canada, CA FICO Full time

About US

FICO, originally known as Fair Isaac Corporation, is a leading analytics and decision management company that empowers businesses and individuals around the world with data-driven insights. Known for pioneering the FICO® Score, a standard in consumer credit risk assessment, FICO combines advanced analytics, machine learning, and sophisticated algorithms to drive smarter, faster decisions across industries. From financial services to retail, insurance, and healthcare, FICO's innovative solutions help organizations make precise decisions, reduce risk, and enhance customer experiences. With a strong commitment to ethical use of AI and data, FICO is dedicated to improving financial access and inclusivity, fostering trust, and driving growth for a digitally evolving world.


The Opportunity

“As a Principal Applied AI Engineer and founding member on our new Generative AI team, you will work at the frontier of language model applications, developing novel solutions for various areas of the FICO platform to include fraud investigation, decision automation, process flow automation, and optimization. You will play a critical role in ensuring robust operation, scalability, and governance of AI systems across our platform. You will have the opportunity to make a meaningful impact on FICO’s platform by infusing it with next-generation AI capabilities. You’ll work with a dedicated team, leveraging your skills in AI and machine learning to build solutions and drive innovation forward.” - Software Engineering – VP.


What You’ll Contribute

  • Design and implement cutting-edge LLM-powered solutions for decision automation, fraud investigation, and process automation within FICO’s platform.
  • Develop sophisticated prompting strategies and Retrieval-Augmented Generation (RAG) architectures tailored to high-stakes applications.
  • Apply advanced fine-tuning, in-context learning techniques, and custom evaluation frameworks to optimize AI model performance.
  • Build robust model evaluation and governance systems, ensuring compliance and reliability across applications.
  • Design and execute comprehensive backtesting methodologies to validate model predictions and performance.
  • Implement A/B testing frameworks to evaluate the impact of various AI interventions on system performance.
  • Monitor model performance and detect drift to maintain high accuracy and relevance over time.
  • Research and integrate the latest AI techniques to keep FICO’s platform at the forefront of innovation.
  • Evaluate new models, architectures, and training approaches, experimenting with emerging technologies to enhance platform capabilities.
  • Develop custom RAG implementations to enhance information retrieval within decision processes.
  • Write production-quality code, implementing machine learning systems with attention to scalability, reliability, and security.
  • Design scalable architectures that support FICO’s analytics and decisioning solutions.
  • Implement advanced monitoring techniques and system reliability checks to maintain operational excellence.


What We’re Seeking

  • 10+ years of industry experience in software, ML or data engineering, with a history of managing complex, large-scale projects and driving strategic technical decisions.
  • In-depth knowledge and experience in fine-tuning, model adaptation, and customization.
  • Solid foundation in machine learning evaluation and testing methodologies, including the development of custom evaluation frameworks.
  • Extensive experience with Retrieval-Augmented Generation (RAG) architectures and familiarity with vector databases
  • Strong hands-on coding in Python, Go, Java, or similar languages.
  • Experience with PyTorch, JAX or similar deep learning frameworks.
  • Knowledge of backtesting methodologies to ensure reliability and robustness of model predictions.
  • Experience with A/B testing frameworks.
  • Expertise in model monitoring, drift detection, and governance to maintain compliance and operational integrity.
  • Proven expertise in modern Large Language Models (LLMs) and their applications preferred.
  • Strong skills in prompt engineering and chain-of-thought prompting techniques.
  • Familiarity with compliance and regulatory technology, particularly in AI-driven decisioning environments.
  • Strong software engineering fundamentals, with experience in writing production-quality code and designing scalable architectures.
  • Proven ability to mentor teams and collaborate across departments to deliver high-impact solutions.
  • Experience in fast-paced environments, with an ability to adapt and drive impact in high-growth, high-stakes settings.
  • Publications, patents, or open-source contributions that showcase thought leadership and technical expertise in AI and machine learning.
  • Bachelor's/Master's/PhD degree in computer science, or a related field with focus in Machine Learning.

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