Manager, Applied AI Science – Healthcare

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

📋 Description

• Oversee, guide, and nurture a small team of Applied AI Scientists while offering technical and scientific direction throughout their projects.

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

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

• Plan and carry out evaluations using representative datasets, reference standards, performance metrics, acceptance criteria, and statistical techniques.

• Establish expected behavior, evaluate outputs and potential failure modes, assess uncertainties and limitations, and suggest enhancements based on evaluation findings.

• Generate maintainable Python code, analytical workflows, evaluation tools, and reusable software components that support AI development and testing.

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

• Remain informed about developments in artificial intelligence, machine learning, statistics, and evaluation methodologies.

• Contribute to the ongoing evolution of practices within the AI Center of Excellence.

• Recruit, mentor, supervise, and evaluate the performance of 2–5 Applied AI Scientists.

⛳️ Requirements

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

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

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

• Experience in Healthcare/CRO is essential.

• Familiarity with GxP, 21 CFR Part 11, HIPAA, GDPR, software validation, or other related regulated-system standards.

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

• Experience in mentoring technical personnel, guiding scientific initiatives, or providing technical leadership across projects.

• Proven experience in applying statistical methods, experimental design, or performance analysis to intricate technical issues.

• Experience in defining AI evaluation metrics, assessing AI control effectiveness, and developing monitoring strategies for AI system performance and risk.

• Proven collaboration skills with software engineers, architects, product teams, and business stakeholders throughout the AI development lifecycle.

• Comprehensive understanding of 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.

• Experience in creating evaluation datasets and reference standards, selecting appropriate metrics, defining acceptance criteria, and analyzing performance and failure modes.

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

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

• Capability to document and convey evaluation methods, assumptions, results, uncertainties, limitations, and recommendations effectively.

• Ability to connect 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 queries.

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

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

• Capacity to work efficiently 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 upholding engineering discipline and operational reliability.

🏝️ Benefits

• Competitive salaries.

• Opportunities for professional advancement.

• RRSP with company matching.*

• Tuition reimbursement.

• Flexible work environment.

• Discretionary Paid Time Off (PTO).

• 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.