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Added 3 days ago
WT
Python & Database Engineer
Wissen Technology
Montreal, QC
- Full-time
We are seeking a Python & Database Engineer with 3–5 years of hands‑on experience in building scalable applications, optimizing databases, and developing automation solutions. The ideal…
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Senior Data Engineer
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Vancouver, BC
Ingest and assemble data from various disparate sources using a variety of tools, including Python and SQL.
Added 3 days ago
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AI LLM Senior Analyst
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- Full-time
Minimum of 2 years of experience as a machine learning engineer or scientist, deploying models in production at scale, including monitoring, alerting, automatic bug filing and auditing.
Added 3 days ago
S
Cloud Support Engineer - Japanese Speaking
Snowflake
ON · Ontario, Canada
- $90,000 to $135,000 USD / year
- Full-time
Solid technical troubleshooting skills, including comfort with SQL, log analysis, and scripting/automation (e.g., Python, APIs, workflow tools) to diagnose issues and streamline tasks.SQL,…
Added 4 days ago
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Senior Engineer (Python/AWS + Azure/React)
Caddie
Toronto, ON
- Full-time
One product, deployed in more than one place: our cloud on AWS, a customer's own Microsoft Azure environment, and, for the most restricted sites, a machine with no internet access. You own…
Added 4 days ago
S
Cloud Support Engineer
Snowflake
Toronto, ON
- $90,000 to $112,000 CAD / year
- Full-time
Solid technical troubleshooting skills, including comfort with SQL, log analysis, and scripting/automation (e.g., Python, APIs, workflow tools) to diagnose issues and streamline tasks.SQL,…
Added 4 days ago
AI
AWS Data Engineer
Apptoza Inc.
Toronto, ON
- Contract
Seeking an experienced AWS Data Engineer to build and support scalable data pipelines and cloud data platforms for banking and financial services applications.
Added 4 days ago
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Data Engineer - DBT Cloud
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Markham, ON
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…inception through warranty 5 years of Snowflake dbtCoreCloud and AWS Cloud Technologies 5 years of experience with coding in multiple programming languages such as PythonJava Deep knowledge…
Added 4 days ago
FT
Lead Software Engineer
Foreseeson Technology
Richmond, BC
- Full-time
We are seeking an out-of-the-box thinking Lead Software Engineer to join our innovative technical projects team. The ideal candidate will have strong expertise in; building code…
Added 4 days ago
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Lead Data Scientist, Innovation Lab
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Calgary, AB
- Full-time
A Lead Applied AI Engineer, your peer, who designs and builds the Lab's generative AI, LLM and agentic systems and gets them into production.
Added 4 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 4 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 4 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 4 days ago
ZC
Machine Learning Engineer
Zurich Canada
Toronto, ON
- Full-time
Relevant experience: Databricks, Spark/PySpark, Delta Lake, Python, SQL, batch/streaming architectures, feature management, data-quality testing, lineage, cloud storage/compute, CI/CD and…
Added 4 days ago
ZC
Machine Learning Engineer
Zurich Canada
Waterloo, ON
- Full-time
Relevant experience: Databricks, Spark/PySpark, Delta Lake, Python, SQL, batch/streaming architectures, feature management, data-quality testing, lineage, cloud storage/compute, CI/CD and…
Added 4 days ago
AW
Data Engineer, Temporary
Aviso Wealth
Remote, Canada
- Temporary
- Remote
Implement modern data and analytics practices using tools such as Databricks, Snowflake, Salesforce, Python, and SQL
Added 4 days ago
AW
Data Engineer, Temporary
Aviso Wealth
Remote, Canada
- Temporary
- Remote
Implement modern data and analytics practices using tools such as Databricks, Snowflake, Salesforce, Python, and SQL
Added 4 days ago
OH
Senior Quality Assurance Engineer
Ontario Health | Santé Ontario
Toronto, ON
- Full-time
The Senior Quality Assurance Engineer is responsible for ensuring the quality, reliability, and performance of digital solutions through manual and automated testing. The role leads testing…
Added 4 days ago
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AI Workflow Engineer
7shifts
Canada
- Full-time
Technical foundation: You have experience building and deploying AI-powered solutions and connecting systems through APIs. You’re comfortable with Python or a similar programming language,…
Added 4 days ago
AI
Senior Software Engineer – Core Java, Apache Spark, Python, SQL, Data Processing
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Montreal, QC
- Full-time
We are seeking a highly motivated and experienced Software Engineer with strong expertise in Core Java, Apache Spark, Python, SQL, and Linux to design, develop, and support scalable…
Added 4 days ago
MC
Data Analyst – Power BI Microsoft Fabric (35903)
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Ottawa, ON
- Full-time
This is an excellent opportunity for a junior-to-mid-level Data Analyst with strong Power BI, SQL and Microsoft data technologies experience who enjoys turning data into meaningful…
Added 4 days ago
PM
Intern, Data Engineer (8 Months)
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Toronto, ON
- Internship
Write SQL or Python scripts to merge and transform datasets.
Added 4 days ago
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Senior Quality Assurance Engineer
Ontario Health
Toronto, ON
- Full-time
The Senior Quality Assurance Engineer is responsible for ensuring the quality, reliability, and performance of digital solutions through manual and automated testing. The role leads testing…
Added 4 days ago
A
Forward Deployed Technical Consultant-Snowflake: AI&Data Advanced Technology Centers
Accenture
Mississauga, ON · Montreal, QC
- Full-time
Design and implement ELT/ETL frameworks using Snowflake SQL, Snowpark Python, Dynamic Tables, Streams, Tasks, and Snowpipe for batch, streaming, CDC, and event-driven ingestion patterns
Added 4 days ago
B
Senior Data Engineer
BMO
Toronto, ON · FCP
- Full-time
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Zurich Canada

Machine Learning Engineer

Waterloo, 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, build, and operationalize secure, scalable machine learning and AI solutions across applied ML, generative AI, data and ML platforms, or MLOps. Collaborate with engineering, data science, architecture, security, governance, and business teams to deliver reliable production systems and establish reusable engineering practices.

Requirements

Candidates should have Python and SQL skills, software engineering fundamentals such as Git, APIs, testing, and CI/CD, and an understanding of machine learning and its development lifecycle. Relevant experience in cloud environments, data processing, and production-ready solutions is expected, with specialization-specific tools and expertise considered assets.

Skills

Python
SQL
Machine Learning
Artificial Intelligence
Model Evaluation
Feature Engineering
Generative AI
Retrieval-Augmented Generation
Databricks
Apache Spark
MLflow
Azure Machine Learning
CI/CD
Docker
Kubernetes
Model Governance

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
Applied AI
Generative AI
Retrieval-Augmented Generation
Azure OpenAI
Databricks
Apache Spark
PySpark
Delta Lake
MLflow
Azure Machine Learning
Azure DevOps
GitHub Actions
Scikit-Learn
PyTorch
TensorFlow
XGBoost
FastAPI
LangChain
Semantic Kernel
Docker
Kubernetes
Terraform
CI/CD
Feature Engineering
Model Evaluation
Responsible AI

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