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Added 17 days ago
HT
Software Validation Technologist
Husky Technologies
Bolton, ON
- Full-time
Implement software validation engineering test plans, cases plus scripts.
Added 17 days ago
NOC Specialist
Rogers Communications
Calgary, AB · Burnaby, BC · North Vancouver, BC · Vancouver, BC · BC · West Vancouver, BC
We're looking for a NOC Specialist to join the Rogers Core-Data Network Operations team. In this role, you will provide operational support and lead incident response and management…
Added 17 days ago
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Data Scientist - Credit Risk (ATH 5531)
TD
Toronto, ON
- Full-time
Use data, analytics, and business insight to identify opportunities, improve credit strategies and customer outcomes, and answer not just "what happened?", but "so what?" and "what should…
Added 17 days ago
BR
Robotics Software Developer – ROS2, State Estimation, Perception
BHF Robotics
Markham, ON
- Full-time
Development Skills: Exceptional C++ / Python programming skills with a strong grasp of modern software engineering practices (Git, CI/CD, unit testing, profiling).
Added 17 days ago
C
Senior AI Engineer
Cloudoplus
ON · Ontario, Canada
- Full-time
…accomplished Senior AI Engineer with 10+ years of enterprise software engineering, machine learning, artificial intelligence, and distributed systems experience to architect, design,…
Added 17 days ago
P
Lead Data Scientist, Innovation Lab
PakEnergy
Calgary, AB
- Full-time
…customer pilots, and for the ML models you own, define the data, monitoring and MLOps requirements for a clean handoff to product and engineering…
Added 17 days ago
CA
Manager – Data Engineering & Platforms
Canadian Addiction Treatment Centers
Markham, ON
- $125,000 to $150,000 CAD / year
- Full-time
…healthcare services across Canada. CATC is is seeking a Manager, Data Engineering & Platforms to lead the development, operation and continuous improvement of CATC's enterprise data…
Added 17 days ago
Q
Machine Learning Engineer, AI Processors
Qualcomm
Markham, ON
- Full-time
Engineering Group, Engineering Group > Machine Learning Engineering
Added 17 days ago
Q
Staff Machine Learning Framework, Complier & Performance Engineer
Qualcomm
Canada
- Full-time
Engineering Group, Engineering Group > Machine Learning Engineering
Added 18 days ago
SM
RQ11486 – Data Ops/Cloud Data Engineer – Senior
S M Software Solutions Inc
Toronto, ON
- Internship
We are seeking a Senior Data Ops/Cloud Data Engineer with extensive experience in designing, developing, automating, and optimizing complex data pipelines and cloud-based data platforms.…
Added 18 days ago
SM
RQ11486 – Data Ops/Cloud Data Engineer – Senior
S M Software Solutions Inc
Toronto, ON
- Internship
We are seeking a Senior Data Ops/Cloud Data Engineer with extensive experience in designing, developing, automating, and optimizing complex data pipelines and cloud-based data platforms.…
Added 18 days ago
SM
RQ11486 – Data Ops/Cloud Data Engineer – Senior
S M Software Solutions Inc
Toronto, ON
- Internship
We are seeking a Senior Data Ops/Cloud Data Engineer with extensive experience in designing, developing, automating, and optimizing complex data pipelines and cloud-based data platforms.…
Added 18 days ago
SM
Python Developer - Hybrid
S M Software Solutions Inc
Mississauga, ON
- Full-time
The Python Developer will develop software solutions using Python, applying strong software engineering principles and data manipulation techniques. The role involves analyzing source code…
Added 18 days ago
SM
Python Developer - Hybrid
S M Software Solutions Inc
Mississauga, ON
- Full-time
The Python Developer will develop software solutions using Python, applying strong software engineering principles and data manipulation techniques. The role involves analyzing source code…
Added 18 days ago
ZC
Machine Learning Engineer
Zurich Canada
Toronto, ON
- Full-time
You will work within a modern cloud data and AI ecosystem and collaborate with Data Engineering, Data Science, Architecture, Governance, Security and business teams to turn data and AI…
Added 18 days ago
ZC
Machine Learning Engineer
Zurich Canada
Waterloo, ON
- Full-time
You will work within a modern cloud data and AI ecosystem and collaborate with Data Engineering, Data Science, Architecture, Governance, Security and business teams to turn data and AI…
Added 18 days ago
SM
Python Developer
S M Software Solutions Inc
Mississauga, ON
- Full-time
We are seeking an experienced Python Developer with 8+ years of experience to design, develop, and maintain software solutions focused on Python programming, data analysis, and large-scale…
Added 18 days ago
C
Ingénieur(e) applications GenAI / agentiques et DevSecOps
CGI
Montreal, QC
- Full-time
Build data pipelines for RAG: ingestion, chunking, embeddings, vector indexing, hybrid search and reranking.
Added 18 days ago
SM
Python Developer - Hybrid
S M Software Solutions Inc
Mississauga, ON
- Full-time
The Python Developer will develop software solutions using Python, applying strong software engineering principles and data manipulation techniques. The role involves analyzing source code…
Added 18 days ago
SM
Python Developer
S M Software Solutions Inc
Mississauga, ON
- Full-time
We are seeking an experienced Python Developer with 8+ years of experience to design, develop, and maintain software solutions focused on Python programming, data analysis, and large-scale…
Added 18 days ago
SM
Python Developer
S M Software Solutions Inc
Mississauga, ON
- Full-time
We are seeking an experienced Python Developer with 8+ years of experience to design, develop, and maintain software solutions focused on Python programming, data analysis, and large-scale…
Added 18 days ago
C
Senior Enterprise Architecture Consultant – Enterprise Modernization
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Vancouver, BC
- Full-time
Guide Python based matching services and related data processing, validation, and stewardship patterns.
Added 18 days ago
GF
Electrical Engineer (Controls and Infrastructure)
General Fusion Inc
Richmond, BC
- $100,000 to $140,000 CAD / year
Bachelor's degree in Electrical Engineering or equivalent, and registration (or eligibility for registration) as a Professional Engineer (P.Eng.) with EGBC.
Added 18 days ago
AW
Data Engineer, Temporary
Aviso Wealth
Remote, Canada
- Temporary
- Remote
Reporting to the Sr Director, Data Platform Delivery and Engineering, the Data Engineer is responsible for designing, building, and collaborating with Development, Security, and TSP Ops…
Added 18 days ago
AW
Data Engineer, Temporary
Aviso Wealth
Remote, Canada
- Temporary
- Remote
Reporting to the Sr Director, Data Platform Delivery and Engineering, the Data Engineer is responsible for designing, building, and collaborating with Development, Security, and TSP Ops…

Zurich Canada

Machine Learning Engineer

Toronto, ON, Canada

The salary range for this position is $92,3000- $151,400 CAD. · Full-time

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Job details

Pay: The salary range for this position is $92,3000- $151,400 CAD.
Job type: Full-time
Apply by: Nov 19, 2026
Experience: As part of a leading global organization, Zurich North America has over 148 years of experience managing risk and supporting resilience.
Posting language: English
Posted: Oct 20, 2026

Original job description

The Opportunity

Are you looking for a caring, collaborative, values-driven workplace with inspiring teammates and leaders? Do you have the ambition and desire to be the best and thrive at the most impactful global insurance provider in the world? Look no further than Zurich Canada.

If you have experience in machine learning, artificial intelligence or ML/AI engineering and are looking for a new challenge, we would love to hear from you.

Zurich Canada is expanding its AI Engineering capability and is looking for Machine Learning / AI Engineers to design, develop and operationalize scalable AI and machine learning solutions.

This posting covers four positions across multiple experience levels, including Junior, Intermediate and Senior opportunities. Candidates will be considered for the appropriate level and specialization based on their experience, technical depth, demonstrated capabilities and scope of responsibility.

You will work within a modern cloud data and AI ecosystem and collaborate with Data Engineering, Data Science, Architecture, Governance, Security and business teams to turn data and AI opportunities into secure, reliable and production-ready solutions.

This is a unique opportunity to build your knowledge and experience for the future in a supportive environment where your voice matters.

What you will do

Areas of Specialization

Candidates may align with one area; experience across all four is not expected.

Machine Learning Engineer - Applied AI

Build/productionize predictive ML/AI: classification, regression, forecasting and clustering.
Build feature pipelines; establish training, validation/testing and bias/fairness testing.
Evaluate models; move experiments to production and optimize inference.
Assess approved A/B, shadow or controlled pilots; monitor data quality, performance/drift and troubleshoot production issues.
Document assumptions, limitations, versions, training-data references and approvals.

Relevant experience: statistical ML; scikit-learn, PyTorch, TensorFlow, XGBoost, LightGBM or CatBoost; feature engineering; model evaluation; time-based validation; leakage prevention; imbalanced datasets; calibration; experiment tracking; batch/real-time inference.

Machine Learning Engineer - Generative AI

Engineer, evaluate and productionize enterprise GenAI using foundation models, retrieval and agentic patterns.
Build LLM services and RAG pipelines covering ingestion, parsing, cleaning, chunking, embeddings, indexing/retrieval.
Evaluate keyword, semantic-vector/hybrid search, filtering/reranking; design prompts, structured outputs/context management.
Improve groundedness through retrieval quality, grounding checks, citations, abstention and human review.
Build controlled agentic workflows/tool integrations; evaluate retrieval, answers, safety, agent behaviour/business outcomes.
Monitor quality, groundedness, safety, latency, reliability/cost; apply access-aware retrieval, sensitive-data controls and prompt-injection defences.
Maintain auditable model, prompt, data, index and evaluation records.

Relevant experience: Azure OpenAI or comparable platforms; RAG; embeddings; vector indexes; BM25; semantic/hybrid search; retrieval/LLM evaluation; prompt engineering; FastAPI; LangGraph, LangChain, Semantic Kernel, Langfuse or OpenTelemetry.

Machine Learning Engineer - Data & ML Platforms

Build/operate enterprise-scale data, feature and engineering foundations for ML/AI.
Develop training and batch/real-time inference pipelines, reusable feature frameworks and batch/streaming components.
Optimize Spark/distributed processing; build secure data-platform/AI interfaces and reusable libraries/templates.
Implement ML dataset quality monitoring; support feature management, lineage/reproducibility.
Engineer large-scale structured/unstructured data; deploy, monitor and troubleshoot production ML data pipelines.

Relevant experience: Databricks, Spark/PySpark, Delta Lake, Python, SQL, batch/streaming architectures, feature management, data-quality testing, lineage, cloud storage/compute, CI/CD and infrastructure as code.

MLOps Engineer

Build/operate platforms, automation and controls across the ML/AI lifecycle.
Design CI/CD for models/AI applications; establish model registration, versioning, lineage/promotion.
Build reproducible training/deployment environments; support staged releases, shadow deployments/rollback.
Monitor health, latency, data quality, model performance/drift; develop retraining/redeployment workflows with validation/approvals.
Manage ML infrastructure/configuration; implement access controls, audit trails/governance evidence and reusable MLOps standards.

Relevant experience: MLflow, Databricks, Azure Machine Learning, Azure DevOps, GitHub Actions, Python, REST APIs, Docker, Kubernetes, Terraform, model registries and production observability.

What you bring to the table

Across the AI Engineering practice, relevant qualifications include:

Python and SQL skills.
Software engineering fundamentals including Git, APIs, testing and CI/CD.
Understanding of ML concepts and the model-development lifecycle.
Experience with data processing and analytical workloads.
Experience in cloud-based development environments.
Understanding of reliable, maintainable, production-ready solutions.

Depending on your specialization, the following are assets:

Databricks, MLflow and Apache Spark/PySpark.
Microsoft Azure or equivalent AWS/Google Cloud technologies.
Azure DevOps or GitHub.
Docker and containerized applications.
REST APIs.
scikit-learn, PyTorch, TensorFlow or comparable ML/deep-learning frameworks.
Azure OpenAI or comparable managed AI platforms.
RAG, embeddings, retrieval and LLM evaluation.
Infrastructure as code, Kubernetes and production observability.
Security, privacy, Responsible AI and model governance in a regulated environment.

Experience Levels

Junior

Work on defined ML/AI engineering tasks with guidance.
Write reliable Python and SQL.
Develop/test components within established architecture and engineering patterns.
Understand core ML and software-engineering practices.
Participate in code reviews and troubleshooting.
Learn Zurich's AI engineering, security and governance standards.

Intermediate

Independently design/deliver ML/AI components and solutions.
Own development through production implementation.
Make appropriate engineering and technology choices.
Troubleshoot complex data, model and production issues.
Contribute to architecture and engineering standards.
Mentor junior team members.
Work with stakeholders to refine technical requirements.

Senior

Lead design/engineering of complex enterprise AI/ML solutions.
Make architecture and technology decisions.
Establish reusable patterns and engineering standards.
Lead production-readiness, scalability, reliability and security decisions.
Mentor engineers and provide technical leadership.
Drive engineering excellence through design/code reviews.
Partner with architecture, security, governance and business leadership.
Evaluate emerging AI technologies and appropriate enterprise adoption patterns.

Compensation

At Zurich Canada, we are committed to pay equity. We determine compensation based on objective criteria such as skills, experience, and internal equity. The salary range for this position is $92,3000- $151,400 CAD.

Our Culture

At Zurich, we are proud of our culture. We are passionate about Diversity, Inclusion, Equity and Belonging (DIEB). We want you to bring your whole self to work, and we want our employees to be reflective of the communities in which we live and work.

We value diverse perspectives and foster a collaborative environment where employees are empowered to make an impact. We offer a comprehensive rewards package designed to support employee well-being, growth, and success.

Comprehensive health and wellness benefits.
Minimum four weeks of vacation annually.
Four personal days each year to support personal, cultural, religious, or well-being needs.
Access to ongoing learning and development opportunities.
Opportunities to support and give back to our communities.
Recognition as one of Greater Toronto's Top Employers and recipient of Insurance Business Canada's 5-Star Diversity, Equity and Inclusion Award.

Make a difference. Be challenged. Be inspired. Be supported. Love what you do. Work for us.

A future with Zurich

Now is the time to move forward and make a difference. At Zurich, we want you to share your unique perspectives, experiences and ideas so we can grow and drive sustainable change together. As part of a leading global organization, Zurich North America has over 148 years of experience managing risk and supporting resilience. We are a leading provider of commercial property-casualty insurance solutions and a wide range of risk management products and services for businesses and individuals. Today, we serve more than 25 industries, from agriculture to technology and insure 90% of the Fortune 500®. Our growth strategy is not limited to our business. As an employer, Zurich strives to provide ongoing career development opportunities and foster an environment where voices are diverse, behaviors are inclusive, actions drive equity, and our people feel a sense of belonging. Be a part of the next evolution of the insurance industry. Join us in building a brighter future for our people, our customers and the communities we serve.

As a global company, Zurich recognizes the diversity of our workforce as an asset. We recruit talented people from a variety of backgrounds with unique perspectives that are truly welcome here. Taken together, diversity and inclusion bring us closer to our common goal: exceeding our customers’ expectations. Zurich is committed to providing a diverse, inclusive and barrier-free environment resulting in an accessible organization for employees, customers, and other parties who interact with, or on behalf of, Zurich. We strive to achieve a workplace free of discrimination of all forms, including discrimination on the basis of physical or mental disability, or medical condition. If you are interested in a job opportunity, please advise if you require an accommodation, so we can work with you to provide a more accessible process.

Zurich does not accept unsolicited resumes from search firms or employment agencies. Any unsolicited resume will become the property of Zurich Canadian Holdings Limited. If you are a preferred vendor, please use our Recruiting Agency Portal for resume submission.

Only applicable for Canada: For Zurich Canada's commitment to diversity and accessibility please click here. If you would prefer to not receive future electronic messages from Zurich Insurance Company Ltd's recruitment management system, please email your request to have your job profile deleted from the system by clicking here. Zurich Insurance Company Ltd 100 King St., W., Suite 5500, Toronto, ON, M5X 1C9. www.zurichcanada.com

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More about this job

Responsibilities

Design, develop, and operationalize scalable AI and machine learning solutions across applied ML, generative AI, data and ML platforms, or MLOps. Collaborate with engineering, data science, architecture, governance, security, and business teams to deliver secure, reliable, production-ready systems.

Requirements

Candidates should have Python and SQL skills, software engineering fundamentals, knowledge of machine learning and its development lifecycle, and experience with data processing and cloud-based development. Specialization-specific experience may include ML frameworks, RAG and LLM systems, Databricks and Spark, or MLOps tools and production infrastructure; the role is available at junior, intermediate, and senior levels.

Skills

Python
SQL
Machine Learning
Artificial Intelligence
Generative AI
MLOps
Data Engineering
Cloud Computing
Model Evaluation
Feature Engineering
Retrieval-Augmented Generation
CI/CD
Databricks
Apache Spark
Azure OpenAI
Responsible AI

Benefits

Health And Wellness Benefits
Minimum Four Weeks Of Vacation Annually
Four Personal Days Each Year
Learning And Development Opportunities
Community Support Opportunities

Visa sponsorship

Not detected in the job text

Keywords

Python
SQL
Machine Learning
Artificial Intelligence
Generative AI
MLOps
Databricks
Apache Spark
PySpark
MLflow
Azure Machine Learning
Azure OpenAI
Scikit-Learn
PyTorch
TensorFlow
XGBoost
LightGBM
CatBoost
Retrieval-Augmented Generation
Embeddings
Vector Indexes
BM25
Semantic Search
FastAPI
LangChain
LangGraph
Docker
Kubernetes
Terraform
CI/CD

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