Jobs / Canada / Astrazeneca Pharmaceuticals Lp

Astrazeneca Pharmaceuticals Lp

AI Associate Principal - Radioconjugate Discovery

Canada – Hamilton – Longwood Road South Posted today

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No sponsorship evidence yet

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No salary bar for this route
Canada has no single salary bar: the employer usually needs a positive LMIA. Pay at or above the provincial median wage + 20% (e.g. C$36.92/h in Ontario) puts it in the high-wage stream. Source: https://www.canada.ca/en/employment-social-development/services/foreign-workers/median-wage.html, rules effective 2026-07-17.

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About the role

Job Title: AI Associate Principal - Radioconjugate Discovery Location: Hamilton, Ontario Onsite 5 days/week   Description: Fusion Pharmaceuticals, part of the AstraZeneca Group, is redefining precision oncology with next‑generation radioconjugates that deliver powerful alpha‑emitting payloads directly to tumors. Our pipeline spans multiple first‑in‑class programs—backed by a GMP‑compliant, brand new radiopharmaceutical facility in Hamilton, we’re turning groundbreaking science into real‑world impact for patients. Join us at the forefront of radiopharma innovation and be part of turning breakthrough science into meaningful outcomes for patients—come build what’s next with us!   The Role: The AI Associate Principal - Radioconjugate Discovery will be accountable for designing, building, deploying, and maintaining software and AI-enabled solutions that accelerate Radioconjugate (RC) Discovery. The AI Associate Principal combines software engineering, data engineering, automation, and applied AI to transform complex scientific workflows into scalable, reliable, and user-friendly tools.   This is a hands-on builder role. You will work directly with RC Discovery scientists to find opportunities, rapidly prototype solutions, and use AI-assisted coding to design, build, test, document, deploy, and maintain production-quality analytical tools. You are expected to write and review code, interrogate data, troubleshoot workflows, and iterate with end users, not solely advise, commission work, or provide strategic oversight.   As an embedded technical leader, you will help shape the RC Discovery AI and data science strategy, establish fit-for-purpose engineering practices, mentor colleagues, and deliver measurable value through improved consistency, efficiency, reproducibility, traceability, and scientific decision-making. You will work closely with Data & AI colleagues, data and software engineers, computational scientists, and scientific partners across imaging, DMPK, safety, translational research, and other relevant collaborators. It will also involve collaboration with cloud, cybersecurity, IT operations, legal, privacy, quality, and compliance teams to ensure that solutions are secure, compliant, maintainable, and fit for purpose.   Responsibilities: • Hands-on AI-assisted software development: Personally design, write, review, test, debug, deploy, and maintain code using modern AI-assisted development approaches. Apply sound software engineering judgment to validate generated code, manage dependencies, protect data integrity, and ensure solutions are scientifically and technically fit for purpose. • Workflow discovery and prioritization: Partner directly with RC Discovery scientists to observe and understand current workflows. Identify recurring difficulties and sources of variability. Prioritize use cases based on scientific value, feasibility, adoption potential, and operational impact. • End-to-end solution delivery: Lead the full lifecycle from problem definition and data exploration through prototyping, model or algorithm development, validation, implementation, user acceptance, release, documentation, training, monitoring, and continuous improvement. • RC Discovery data and analytics: Develop solutions that integrate, analyze, and visualize structured and unstructured discovery data. Potential applications include biodistribution, imaging, radiochemistry, in vitro and in vivo assay data, immunohistochemistry (IHC), PK/PD and dosimetry-related analyses, automated quality control, scientific reporting, and decision-support workflows. • Applied AI and intelligent automation: Leverage AI, machine learning, large language models, statistical methods, and other computational approaches when they provide clear value. Prioritize pract

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