Manager, Applied AI Science – Healthcare

This is a fully remote position, open to applicants in Canada.

📋 Description

• Oversee, mentor, and cultivate a small team of Applied AI Scientists.

• Offer technical and scientific expertise throughout the team's initiatives.

• Create, develop, and enhance reusable AI capabilities utilizing machine learning, large language models, retrieval-augmented generation, AI agents, and recognized enterprise AI technologies.

• Develop solutions that integrate models, prompts, context, retrieval, tools, structured outputs, human review, and workflow integration.

• Design and implement scientific evaluations using representative datasets, reference standards, performance metrics, acceptance criteria, and statistical methods.

• Establish expected behavior, analyze outputs and failures, evaluate uncertainty and limitations, and suggest evidence-based enhancements.

• Produce maintainable Python code, analytical workflows, evaluation tools, and reusable software components.

• Collaborate with AI Architecture, Product Management, application teams, subject matter experts, Quality, and Governance.

• Ensure AI capabilities meet operational requirements and make progress toward enterprise utilization.

• Remain updated on advancements in artificial intelligence, machine learning, statistics, and evaluation techniques.

• Contribute to the advancement of practices within the AI Center of Excellence.

• Recruit, mentor, guide the work of, and manage the performance of 2–5 Applied AI Scientists.

⛳️ Requirements

• Master's degree in Computer Science, Data Science, Statistics, Biomedical Engineering, Applied Mathematics, Computer Engineering, or a related quantitative field.

• A Bachelor's degree in a related quantitative discipline with considerable applied AI, machine learning, or statistical experience will also be considered.

• Over 5 years of experience in developing AI, machine learning, data science, or applied AI solutions in practical settings.

• Must have experience in Healthcare/CRO.

• Knowledge of GxP, 21 CFR Part 11, HIPAA, GDPR, software validation, or similar regulated-system requirements.

• Strong programming skills in Python, R, or a similar language.

• Experience mentoring technical staff, leading scientific projects, or providing technical guidance across various initiatives.

• Proficient in applying statistical methods, experimental design, or performance analysis to intricate technical challenges.

• Experience in defining AI evaluation metrics, evaluating the efficiency of AI controls, and creating monitoring strategies for AI system performance and risk.

• Proven ability to collaborate with software engineers, architects, product teams, and business stakeholders throughout the AI development lifecycle.

• Strong foundation in statistics, experimental design, sampling, machine learning, model validation, uncertainty, bias, and generalizability.

• Experience in developing capabilities using large language models, retrieval-augmented generation, prompt and context design, AI agents, tool integration, and structured outputs.

• Familiarity with developing evaluation datasets and reference standards, selecting suitable metrics, defining acceptance criteria, and analyzing performance and failure modes.

• Strong programming capabilities with the aptitude to create maintainable analytical software, AI functionalities, and evaluation tools.

• Understanding of how models, data, retrieval, prompts, tools, human review, and workflow context interact to influence AI system behavior.

• Ability to document and articulate evaluation methods, assumptions, results, uncertainties, limitations, and suggestions.

• Capacity to link technical decisions to enterprise architecture, long-term reuse, scalability, and business strategy.

• Skill in translating operational requirements and workflows into structured AI capabilities and measurable evaluation inquiries.

• Advanced problem-solving ability to address intricate architecture and engineering challenges through practical and sustainable solutions.

• Proficiency in clearly communicating architectural concepts, trade-offs, and recommendations to executives, engineers, scientists, architects, and business stakeholders.

• Capability to work effectively across Product Management, AI Science, Application Development, Platform Engineering, DevOps, Security, Data, Quality, and business teams.

• Ability to assess emerging technologies and adapt architectural direction while ensuring engineering discipline and operational reliability.

🏝️ Benefits

• Competitive salaries.

• Opportunities for career advancement.

• 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.