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Added 4 months ago
EN
Distinguished SW Systems Engineer (10343)
Extreme Networks
Toronto, ON
- Full-time
Added 4 months ago
L
Engineering Manager, Lime Vision
Lime
Remote, Canada
- $172,000 to $237,000 CAD / year
- Full-time
- Remote
Experience building, deploying, and operating ML systems in production, including edge AI environments and modern MLOps practices.
Added 4 months ago
KC
Forward Deployed AI Engineer
Keyrus Canada
Toronto, ON · Montreal, QC
- Full-time
Added 4 months ago
B
Data Scientist, Tax Transformation Office
BDO
Toronto, Ontario
- Full-time
Experience with MLOps, model deployment, APIs, and scalable AI infrastructure considered an asset
Added 1 month ago
IF
Senior Full-Stack Software Developer (Python/React)
Intact FC
Toronto, ON · Montreal, QC
- Full-time
We’re looking for a Senior Full-Stack Software Developer (Python/React) to join our growing AI Engineering team and build reliable, scalable AI-powered products across distributed systems,…
Added 4 months ago
P
AI Engineer
Portless
Remote, Canada
- Remote
Added 4 months ago
US
Senior Data & AI Consultant/Consulting Lead (Montreal, Canada)
Unit8 SA
Remote, Canada
- Full-time
- Remote
Shape the critical enablers that make data and AI work at scale, such as data & AI governance, LLMOps and MLOps, responsible, compliant AI, and the operating models behind data and AI…
Added 5 months ago
Senior Data Platform Engineer
Helcim Inc
Calgary, Alberta
…platform. You’ll work hands-on across our data infrastructure, MLOps/AI tooling, governance practices, and real-time modeling and monitoring capabilities, while establishing the standards…
Added 5 months ago
S
Staff Machine Learning Engineer, AI Generation Engine
SandboxAQ
Remote, Canada
- $146,200 to $258,000 CAD / year
- Full-time
- Remote
Deep proficiency in MLOps and software best practices, including CI/CD for ML, experiment tracking (e.g., Weights & Biases, MLflow), automated testing, and version control for both code and…
Added 5 months ago
S
Senior Machine Learning Engineer, AI Generation Engine
SandboxAQ
Remote, Canada
- $119,000 to $210,000 CAD / year
- Full-time
- Remote
Deep proficiency in MLOps and software best practices, including CI/CD for ML, experiment tracking (e.g., Weights & Biases, MLflow), automated testing, and version control for both code and…
Added 4 months ago
B
Solution Architect, AI
BRP
Montreal, Quebec
- Full-time
Familiarity with MLOps concepts: model lifecycle, versioning, deployment, monitoring.
Added 5 months ago
P
Principal Enterprise Architect, AI Platform
Priceline
Toronto, Ontario
- Full-time
Define Platform Standards: Deliver "golden paths" and reusable frameworks (e.g., multi-agent frameworks like LangChain/LangGraph) to improve developer productivity for AI use cases.
Added 1 month ago
Staff Software Engineer, Machine Learning Platform
Stripe
Toronto, ON
Drive cross-team technical initiatives that improve ML development velocity and MLOps maturity across the company.
Added 4 months ago
B
Solution Architect, AI
BRP
Montreal, Quebec
- Full-time
Familiarity with MLOps concepts: model lifecycle, versioning, deployment, monitoring.
Added 1 month ago
DevOps Engineer
Later
Vancouver, BC
Help evaluate and adopt DevOps and MLOps tools that improve system efficiency, observability, developer experience, model deployment, and operational reliability.
Added 2 months ago
SP
Applied AI Engineer
Singapore Post
Montreal, QC
- Full-time
Scalable MLOps Architecture: Develop and maintain robust agentic frameworks ensuring the infrastructure can scale to meet the demands of various strategic partners.
Added 3 months ago
AI Developer/Prompt Engineer
Levio
Toronto, Ontario
We are seeking AI Developer /Prompt Engineer to contribute to major projects.
Added 5 months ago
H
AI Engineer - Remote
Huzzle
Remote, Canada
- Full-time
- Remote
Knowledge of MLOps and model monitoring tools.
Added 5 months ago
H
Applied AI Scientist (Hybrid)
Homebase
Remote, Canada
- $108,000 to $130,000 CAD / year
- Full-time
- Remote
Added 5 months ago
O
Senior Software Developer, Data & MLOps
OSEDEA
Montreal, Quebec
- Full-time
As a Senior Software Developer with strong Data Engineering and MLOps experience, you design, build, and deliver robust data and machine learning solutions for our clients. You combine…
Added 5 months ago
S
Senior Software Engineer II
SurveyMonkey
Remote, Canada
- $126,400 to $158,000 CAD / year
- Full-time
- Remote
Added 5 months ago
T
Machine Learning Engineer II
TD
Remote, Canada
- Full-time
- Remote
Strong technical skills: machine learning, data engineering, MLOps, cloud solution architecture, software development practices
Added 5 months ago
B
Senior Platform Systems Engineer
Bettermode
Toronto, Ontario
- Full-time
Added 5 months ago
C
AI Engineer
Chubb
Toronto, ON
- Full-time
…streamline LLM and generative AI workflows while driving adoption of MLOps best practices, including CI/CD pipelines, versioning, testing, and model…
Added 5 months ago
IE
Senior Machine Learning Engineer
Index Exchange
Toronto, Ontario
- Full-time
Design and implement enterprise-scale MLOps systems and platforms (including data ingestion, feature pipelines, model training, validation, deployment and monitoring), setting standards for…

Chubb

AI Engineer

199 Bay Street, Suite 2500, Toronto, ON, M5L 1E2, Canada

Full-time

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Job details

Job type: Full-time
Experience: 2 - 5 years’ experience in AI Engineering and/or Machine Learning (ML) with a focus on LLMs, with deep expertise in writing, and reviewing production code in Python
Posting language: English
Posted: May 4, 2026

Original job description

KEY OBJECTIVES:

We are seeking a highly skilled AI Engineer to lead the design, solutioning, and development of scalable, reusable AI-driven core capabilities for our global Finance Transformation program. This role sits at the intersection of finance, technology, and governance, enabling the development of intelligent, compliant-by-design solutions that support key Finance functions at a global level.

You will partner closely with cross-functional teams including Finance, IT, Global Analytics, Legal, Compliance, and Risk to deliver secure, scalable, and regulatory-aligned AI solutions across the enterprise.

MAJOR RESPONSIBILITIES:

Lead the architecture, design, and development of AI/ML solutions at a global level to support finance and controllership processes (e.g., close, reconciliation, reporting, anomaly detection etc).
Build scalable, reusable core AI capabilities that can be leveraged across multiple finance use cases and geographies.
Translate business requirements into robust technical solutions, ensuring alignment with enterprise architecture and data strategy.
Collaborate with Finance, IT, Data & Analytics, Legal, Compliance, Security, Enterprise Architecture and Risk teams to design and implement compliant-by-design AI solutions.
Ensure adherence to regulatory requirements, data privacy laws, and internal governance frameworks.
Develop and deploy models using modern AI/ML frameworks; ensure model performance, monitoring, and lifecycle management.
Identify opportunities to automate and optimize finance processes using AI (e.g., intelligent automation, NLP, predictive analytics).
Provide technical leadership and mentorship to junior engineers and cross-functional teams.
Ensure high quality code that meets business objectives, quality standards and development guidelines.
Building reusable pipelines, processes, and tools to streamline LLM and generative AI workflows while driving adoption of MLOps best practices, including CI/CD pipelines, versioning, testing, and model governance.
Manage project stakeholder expectations and issue communications on progress.
React to shifting priorities without compromising deadlines and momentum.
Stay current with emerging AI technologies and assess their applicability within finance and risk-controlled environments.

Qualifications

QUALIFICATIONS:

Must have:
- 2 - 5 years’ experience in AI Engineering and/or Machine Learning (ML) with a focus on LLMs, with deep expertise in writing, and reviewing production code in Python
- Understanding the development lifecycle for LLMs - developing data sets for pre-training, instruction tuning, and preference alignment alongside the modelling techniques for each stage and LLM deployment is as MAJOR plus
- Strong knowledge of LLM frameworks and libraries (such as transformers, trl, deepspeed, PyTorch), and exposure to various ML techniques and their practical implementation in production at large scale
- Experience building and deploying solutions on cloud platforms (AWS, Azure, or GCP)
- Experience on distributed, high throughput and low latency architectures
- Strong fundamentals in NLP techniques for text representation, semantic extraction techniques, data structures and modeling
- Experience building software on top of major container technology (Kubernetes, Docker etc.)
- Knowledge of version control using Jenkins, GitHub Actions, GitLab CI, Jenkins, or Azure DevOps
- Solid understanding of data engineering concepts and working with large-scale datasets
- Experience implementing ML Ops practices and production-grade AI systems
- Familiarity with data privacy, model governance, and responsible AI principles

Nice to have:
- Experience and Knowledge of Finance Domain: Understanding of finance concepts, workflows, or platforms is a strong asset for this role along with Knowledge of financial processes such as close, consolidation, reporting, and audit
- Exposure to regulatory and compliance frameworks (e.g., SOX, GDPR, model risk management)
- Experience with ERP systems (e.g., SAP, Oracle) and finance data ecosystems
- Experience defining system architecture and exploring technical feasibility tradeoffs is a plus
- Strong understanding of AI risk, explainability, and auditability
- Familiarity with end-to-end application development using full stack is a plus
- Experience in P&C insurance is a plus

Key Competencies:
- Strong problem-solving and analytical thinking
- Ability to work across cross-functional and global teams
- Excellent communication and stakeholder management skills
- High attention to governance, risk, and compliance considerations
- Ability to balance innovation with control and scalability

What Success Looks Like:
- Delivery of scalable AI capabilities embedded within finance processes
- Measurable improvements in key KPIS - efficiency, accuracy, and compliance
- Strong adoption of AI solutions across finance teams globally
- Robust governance and audit-ready AI implementations

Chubb Canada does not use artificial intelligence (AI) tools to assess, screen, or select applicants.

At Chubb we are committed to providing equal employment opportunities to all employees and applicants. It is our policy to provide equal employment opportunities to employees and applicants based on job-related qualifications and ability to perform a job. If you require accommodation during the hiring process or upon hire, please inform Human Resources. If a selected applicant requests accommodation during the recruitment process, Chubb will consult with the applicant in order to provide suitable accommodation that takes into account the applicant’s accessibility needs.

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More about this job

Responsibilities

Lead the design and development of scalable, compliant AI/ML solutions to optimize global finance and controllership processes. Collaborate with cross-functional teams to implement reusable AI capabilities and MLOps best practices across the enterprise.

Requirements

Requires 2-5 years of experience in AI/ML with deep expertise in Python and LLM frameworks like PyTorch and Transformers. Candidates should have experience with cloud platforms, containerization, and a strong understanding of NLP and data engineering.

Skills

AI Engineering
Machine Learning
Large Language Models
Python
PyTorch
Cloud Platforms
NLP
Kubernetes
Docker
MLOps
Data Engineering
Model Governance
CI/CD
Distributed Architectures
Financial Analysis
Stakeholder Management

Visa sponsorship

Not detected in the job text

Keywords

AI
Machine Learning
LLM
Python
PyTorch
Transformers
TRL
DeepSpeed
AWS
Azure
GCP
Kubernetes
Docker
Jenkins
GitHub Actions
GitLab CI
Azure DevOps
MLOps
NLP
Finance Transformation
SOX
GDPR
SAP
Oracle
P&C Insurance
Model Risk Management
CI/CD
Data Privacy
Responsible AI
Distributed Architecture

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