We are seeking an experienced Senior Data Science Developer to lead the technical design, development, and implementation of enterprise Artificial Intelligence (AI) solutions, Generative AI applications, and autonomous intelligent agents. In this role, you will accelerate the delivery of strategic AI use cases by creating reusable services, comp
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onents, APIs, and solution patterns that reduce reliance on one-off implementations. Leveraging advanced Python software engineering, retrieval-augmented generation (RAG), agentic workflows, and the Azure AI/Microsoft Foundry ecosystem, you will build scalable prototypes, transition proofs of concept into hardened production environments, and collaborate closely with cross-functional technical teams to implement secure, ethical, and high-performing AI capabilities.
Location: Toronto, ON (Hybrid – 3 days a week onsite)
Duration: 6-month contract.
Advantages
Modern Agentic & GenAI Stack: Hands-on development utilizing LLMs, RAG, agentic AI, and Azure AI Foundry.
Production-Grade Engineering: Build scalable, reusable services and APIs rather than isolated proofs of concept.
Modern Cloud Ecosystem: Direct exposure to Azure OpenAI, Microsoft Copilot Studio, Azure ML, and Databricks.
Hybrid Flexibility: Balanced hybrid schedule working 3 days a week onsite in Toronto.
Responsibilities
Design, build, test, and deploy production-grade Generative AI applications, intelligent agents, and machine learning solutions for priority business use cases.
Develop modular and reusable AI components, RESTful services, APIs, and architectural patterns that can be scaled across diverse business domains.
Implement advanced AI techniques incorporating Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), autonomous agentic workflows, and predictive machine learning models.
Seamlessly integrate AI and machine learning solutions with enterprise data sources, cloud data platforms, backend applications, and business workflows.
Construct functional prototypes and rapid proofs of concept (PoCs), validating feasibility before evolving them into secure, scalable, and observable production deployments.
Apply disciplined software engineering standards, including source code version control (Git), automated testing, CI/CD pipelines, runtime monitoring, and performance optimization.
Evaluate and benchmark AI solution performance, reliability, token usage, precision, and scalability using structured model evaluation methodologies.
Incorporate Responsible AI frameworks, data privacy rules, information security guardrails, and enterprise governance controls throughout the solution lifecycle.
Partner with Product Managers, Data Scientists, Data Engineers, and Data Architects to translate business requirements into working technical solutions.
Author technical documentation, maintain development guidelines, and conduct knowledge transfer sessions to build internal engineering capabilities.
Qualifications
Advanced AI & Python Engineering: Advanced hands-on expertise in Python, robust software engineering practices, LLMs, RAG architectures, agentic AI, APIs, prompt engineering, model evaluation, and production-level AI development (Strictly Required).
Azure AI & Cloud Ecosystem: Strong practical experience with Microsoft Foundry / Azure AI Foundry, Azure Machine Learning, Azure AI services, Azure OpenAI, and cloud-based AI solution engineering (Strictly Required).
Machine Learning & Statistical Foundation: Strong technical foundation in statistics and machine learning, including classification, regression, clustering, feature engineering, validation techniques, and ML pipelines delivering measurable performance (Strictly Required).
Tooling & Platform Proficiency: Demonstrated proficiency across the core technical stack: Python, SQL, Databricks, Power Automate, VS Code, Git, and Jira (Strictly Required).
Software Engineering Discipline: Demonstrated proficiency with version control, unit/integration testing, containerization, and continuous integration/continuous deployment (CI/CD) pipelines (Strictly Required).
Responsible AI & Governance: Solid understanding of data governance, data privacy, security protocols, and Responsible AI principles applied to model deployment (Strictly Required).
Education & Professional Experience: Degree in Computer Science, Data Science, Engineering, Artificial Intelligence, or a related technical discipline, or equivalent practical experience (Strictly Required).
Nice-to-Have Assets:
Prior experience delivering AI, machine learning, or advanced data science solutions within the public sector.
Relevant cloud or AI certifications (e.g., Azure AI Engineer Associate, Azure Data Scientist Associate).
Practical experience building custom enterprise Copilots using Microsoft Copilot Studio.
Summary
If you're interested in the "Senior Data Science Developer" role based in Toronto, we encourage you to apply online at www.randstad.ca.
Only qualified candidates will be contacted for the next steps. We look forward to hearing from you!
Randstad Canada is committed to fostering a workforce reflective of all peoples of Canada. As a result, we are committed to developing and implementing strategies to increase the equity, diversity and inclusion within the workplace by examining our internal policies, practices, and systems throughout the entire lifecycle of our workforce, including its recruitment, retention and advancement for all employees. In addition to our deep commitment to respecting human rights, we are dedicated to positive actions to affect change to ensure everyone has full participation in the workforce free from any barriers, systemic or otherwise, especially equity-seeking groups who are usually underrepresented in Canada's workforce, including those who identify as women or non-binary/gender non-conforming; Indigenous or Aboriginal Peoples; persons with disabilities (visible or invisible) and; members of visible minorities, racialized groups and the LGBTQ2+ community.
Randstad Canada is committed to creating and maintaining an inclusive and accessible workplace for all its candidates and employees by supporting their accessibility and accommodation needs throughout the employment lifecycle. We ask that all job applications please identify any accommodation requirements by sending an email to accessibility@randstad.ca to ensure their ability to fully participate in the interview process.
This posting is for existing and upcoming vacancies.
show more
We are seeking an experienced Senior Data Science Developer to lead the technical design, development, and implementation of enterprise Artificial Intelligence (AI) solutions, Generative AI applications, and autonomous intelligent agents. In this role, you will accelerate the delivery of strategic AI use cases by creating reusable services, components, APIs, and solution patterns that reduce reliance on one-off implementations. Leveraging advanced Python software engineering, retrieval-augmented generation (RAG), agentic workflows, and the Azure AI/Microsoft Foundry ecosystem, you will build scalable prototypes, transition proofs of concept into hardened production environments, and collaborate closely with cross-functional technical teams to implement secure, ethical, and high-performing AI capabilities.
Location: Toronto, ON (Hybrid – 3 days a week onsite)
Duration: 6-month contract.
Advantages
Modern Agentic & GenAI Stack: Hands-on development utilizing LLMs, RAG, agentic AI, and Azure AI Foundry.
Production-Grade Engineering: Build scalable, reusable services and APIs rather than isolated proofs of concept.
...
Modern Cloud Ecosystem: Direct exposure to Azure OpenAI, Microsoft Copilot Studio, Azure ML, and Databricks.
Hybrid Flexibility: Balanced hybrid schedule working 3 days a week onsite in Toronto.
Responsibilities
Design, build, test, and deploy production-grade Generative AI applications, intelligent agents, and machine learning solutions for priority business use cases.
Develop modular and reusable AI components, RESTful services, APIs, and architectural patterns that can be scaled across diverse business domains.
Implement advanced AI techniques incorporating Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), autonomous agentic workflows, and predictive machine learning models.
Seamlessly integrate AI and machine learning solutions with enterprise data sources, cloud data platforms, backend applications, and business workflows.
Construct functional prototypes and rapid proofs of concept (PoCs), validating feasibility before evolving them into secure, scalable, and observable production deployments.
Apply disciplined software engineering standards, including source code version control (Git), automated testing, CI/CD pipelines, runtime monitoring, and performance optimization.
Evaluate and benchmark AI solution performance, reliability, token usage, precision, and scalability using structured model evaluation methodologies.
Incorporate Responsible AI frameworks, data privacy rules, information security guardrails, and enterprise governance controls throughout the solution lifecycle.
Partner with Product Managers, Data Scientists, Data Engineers, and Data Architects to translate business requirements into working technical solutions.
Author technical documentation, maintain development guidelines, and conduct knowledge transfer sessions to build internal engineering capabilities.
Qualifications
Advanced AI & Python Engineering: Advanced hands-on expertise in Python, robust software engineering practices, LLMs, RAG architectures, agentic AI, APIs, prompt engineering, model evaluation, and production-level AI development (Strictly Required).
Azure AI & Cloud Ecosystem: Strong practical experience with Microsoft Foundry / Azure AI Foundry, Azure Machine Learning, Azure AI services, Azure OpenAI, and cloud-based AI solution engineering (Strictly Required).
Machine Learning & Statistical Foundation: Strong technical foundation in statistics and machine learning, including classification, regression, clustering, feature engineering, validation techniques, and ML pipelines delivering measurable performance (Strictly Required).
Tooling & Platform Proficiency: Demonstrated proficiency across the core technical stack: Python, SQL, Databricks, Power Automate, VS Code, Git, and Jira (Strictly Required).
Software Engineering Discipline: Demonstrated proficiency with version control, unit/integration testing, containerization, and continuous integration/continuous deployment (CI/CD) pipelines (Strictly Required).
Responsible AI & Governance: Solid understanding of data governance, data privacy, security protocols, and Responsible AI principles applied to model deployment (Strictly Required).
Education & Professional Experience: Degree in Computer Science, Data Science, Engineering, Artificial Intelligence, or a related technical discipline, or equivalent practical experience (Strictly Required).
Nice-to-Have Assets:
Prior experience delivering AI, machine learning, or advanced data science solutions within the public sector.
Relevant cloud or AI certifications (e.g., Azure AI Engineer Associate, Azure Data Scientist Associate).
Practical experience building custom enterprise Copilots using Microsoft Copilot Studio.
Summary
If you're interested in the "Senior Data Science Developer" role based in Toronto, we encourage you to apply online at www.randstad.ca.
Only qualified candidates will be contacted for the next steps. We look forward to hearing from you!
Randstad Canada is committed to fostering a workforce reflective of all peoples of Canada. As a result, we are committed to developing and implementing strategies to increase the equity, diversity and inclusion within the workplace by examining our internal policies, practices, and systems throughout the entire lifecycle of our workforce, including its recruitment, retention and advancement for all employees. In addition to our deep commitment to respecting human rights, we are dedicated to positive actions to affect change to ensure everyone has full participation in the workforce free from any barriers, systemic or otherwise, especially equity-seeking groups who are usually underrepresented in Canada's workforce, including those who identify as women or non-binary/gender non-conforming; Indigenous or Aboriginal Peoples; persons with disabilities (visible or invisible) and; members of visible minorities, racialized groups and the LGBTQ2+ community.
Randstad Canada is committed to creating and maintaining an inclusive and accessible workplace for all its candidates and employees by supporting their accessibility and accommodation needs throughout the employment lifecycle. We ask that all job applications please identify any accommodation requirements by sending an email to accessibility@randstad.ca to ensure their ability to fully participate in the interview process.
This posting is for existing and upcoming vacancies.
show more
