[Hiring] Manager, Applied AI Science @United Biosource Corporation

Role Description

Join UBC’s AI Center of Excellence as a Manager, Applied AI Science, where you will lead a small team of Applied AI Scientists while remaining a hands-on technical contributor responsible for designing, developing, and scientifically evaluating reusable AI capabilities that are reliable, measurable, explainable, and appropriate for their intended use.

You will partner with AI Architecture, Product Management, application teams, and business subject matter experts to translate operational needs into effective AI capabilities and measurable performance expectations. You will guide the scientific approach used to evaluate these capabilities, characterize their strengths and limitations, and use empirical evidence to improve their reliability and readiness for broader enterprise use.

Specific Job Duties

• Applied AI Science Leadership: Lead, mentor, and develop a small team of Applied AI Scientists and provide technical and scientific guidance across their work.
• AI Capability Development: Design, develop, and refine reusable AI capabilities using machine learning, large language models, retrieval-augmented generation, AI agents, and other approved enterprise AI technologies.
• AI System Design: Design solutions that combine models, prompts, context, retrieval, tools, structured outputs, human review, and workflow integration to support defined intended uses.
• Scientific Evaluation: Design and execute evaluations using representative datasets, reference standards, appropriate performance metrics, acceptance criteria, and statistical methods.
• AI Behavior and Performance Analysis: Define expected behavior, analyze outputs and failure modes, assess uncertainty and limitations, and recommend improvements based on evaluation evidence.
• Programming and Technical Implementation: Develop maintainable Python code, analytical workflows, evaluation tools, and reusable software components supporting AI development and testing.
• Collaboration: Work with AI Architecture, Product Management, application teams, subject matter experts, Quality, and Governance to ensure capabilities address operational needs and can progress toward enterprise use.
• Continuous Improvement: Stay current on advancements in artificial intelligence, machine learning, statistics, and evaluation methods, and contribute to evolving practices within the AI Center of Excellence.
• Supervisory Responsibility: Directly responsible for hiring, mentoring, work direction, and performance management of a small group (2-5) of Applied AI Scientists.

Qualifications

• Master's degree in Computer Science, Data Science, Statistics, Biomedical Engineering, Applied Mathematics, Computer Engineering, or a related quantitative discipline.
• Bachelor's degree in a related quantitative discipline with significant applied AI, machine learning, or statistical experience will also be considered.

Requirements

• 5+ years of experience developing AI, machine learning, data science, or applied AI solutions in applied environments.
• Must have Healthcare/CRO experience and familiarity with GxP, 21 CFR Part 11, HIPAA, GDPR, software validation, or related regulated-system expectations.
• Strong programming experience using Python, R, or a comparable language.
• Experience mentoring technical staff, leading scientific work, or providing technical direction across projects.
• Experience applying statistical methods, experimental design, or performance analysis to complex technical problems.
• Experience defining AI evaluation metrics, assessing the effectiveness of AI controls, and developing monitoring approaches for AI system performance and risk.
• Experience collaborating with software engineers, architects, product teams, and business stakeholders throughout the AI development lifecycle.

Technical Expertise

• Statistics and Machine Learning: Strong understanding of statistics, experimental design, sampling, machine learning, model validation, uncertainty, bias, and generalizability.
• Generative AI: Experience developing capabilities using large language models, retrieval-augmented generation, prompt and context design, AI agents, tool integration, and structured outputs.
• AI Evaluation: Experience developing evaluation datasets and reference standards, selecting appropriate metrics, defining acceptance criteria, and analyzing performance and failure modes.
• Programming: Strong programming skills with the ability to develop maintainable analytical software, AI capabilities, and evaluation tooling.
• AI System Design: Understanding of how models, data, retrieval, prompts, tools, human review, and workflow context combine to shape AI system behavior.
• Scientific Communication: Ability to document and communicate evaluation methods, assumptions, results, uncertainty, limitations, and recommendations.

Preferred Qualifications

• Previous direct AI management experience.
• Peer-reviewed publications, conference presentations, patents, or other demonstrated scientific contributions.
• Experience using Claude Code, GitHub Copilot, Cursor, or similar agentic development tools.
• Experience with Azure AI, Azure OpenAI, Snowflake Cortex AI, LangGraph, Model Context Protocol, or comparable enterprise AI technologies.
• Experience developing supervised or unsupervised machine learning models.

Additional Skills

• Strategic Thinking: Ability to connect technical decisions to enterprise architecture, long-term reuse, scalability, and business strategy.
• Problem Framing: Ability to translate operational needs and workflows into structured AI capabilities and measurable evaluation questions.
• Problem Solving: Advanced ability to resolve complex architecture and engineering challenges through practical and maintainable solutions.
• Communication: Ability to communicate architectural concepts, tradeoffs, and recommendations clearly to executives, engineers, scientists, architects, and business stakeholders.
• Collaboration: Ability to work effectively across Product Management, AI Science, Application Development, Platform Engineering, DevOps, Security, Data, Quality, and business teams.
• Adaptability: Ability to evaluate emerging technologies and evolve architectural direction while maintaining engineering discipline and operational reliability.

Benefits

• Competitive salaries
• Growth opportunities for promotion
• RRSP with company match*
• Tuition reimbursement
• Flexible work environment
• Discretionary PTO (Paid Time Off)
• Paid Holidays
• Employee assistance programs
• Medical, Dental, and vision coverage
• Telemedicine (Virtual doctor appointments)
• Wellness program
• Adoption assistance
• Short term disability
• Long term disability
• Life insurance
• Discount programs