Jobs in Vaughan, ON and nearby

Jobs within 25 km of Vaughan, ON, Canada. Nearby towns and cities are included. Distances are straight-line, not driving distances.

45,988 listings · 6,539 employers Counted Oct 3, 2026. How we count

About these jobs

Employers hiring include Loblaw Companies Limited (627 listings), Scotiabank (615 listings), TD (391 listings).

Common roles: Software engineer, Retail sales associate, Project manager.

6,688 of these listings include employer-provided pay. Open a job to see its currency and pay period.

Advertised starting pay
Pay period	Median starting pay	Listings
CAD / year	85,000.00	4,047
CAD / hour	23.65	1,916
USD / year	120,000.00	357
USD / hour	20.00	103
GBP / hour	35.00	14
CAD / month	4,054.00	12
CAD / week	868.50	12

Employer-listed minimums from at least 10 listings per currency and pay period. These are advertised starting amounts, not employee salaries. Jobs without a minimum and unusual amounts are excluded.

Workplace classifications: 0% remote, 29% hybrid, 70% on-site, 0% not specified. Hybrid and on-site classifications may be inferred from descriptions. Check the original ad.

Based on the dated count above. Listings can change. How we count

Jobs in Vaughan, ON and nearby

Within 25 km

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Added 9 hours ago
Business Analyst II - Senior Pharmacy Operations
TELUS
Toronto, ON
Added 9 hours ago
TT
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Toronto, ON
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Toronto, ON
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AH
Quality Engineer - 12 Months Contract
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Toronto, ON
- $80,000 to $90,000 CAD / year
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WO
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Toronto, ON
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Social Worker - Supportive Care
University Health Network
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QN
In home Personal Support Worker - Hoyer lift experience
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Toronto, ON
- $19 to $23 CAD / hour
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Added 9 hours ago
Staff Software Engineer, User Targeting
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Toronto, ON
Added 9 hours ago
AC
Accounts Receivable Specialist
Aston Carter
Toronto, ON
- $65,000 to $80,000 CAD / year
- Full-time
Added 9 hours ago
Senior Software Engineer I, Core Objects
Braze
Toronto, ON
Added 9 hours ago
E
Director of Engineering
Experis
Toronto, ON
- $180,000 to $205,000 CAD / year
- Full-time

Lorven Technologies Inc.

Machine Learning Engineer

Toronto, ON, Canada

Contract

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Applications open in a new tab.

Job details

Job type: Contract
Apply by: Oct 29, 2026
Posting language: English
Posted: Sep 29, 2026

Original job description

Job Title: Senior Machine Learning Engineer for AI platform

Location: Toronto, ON, Canada (Hybrid)

Domain: Enterprise SaaS | Artificial Intelligence & Machine Learning | Regulated Financial Services

Role Overview

The Senior Machine Learning Engineer is a core technical practitioner responsible for designing, building, and deploying production-grade Machine Learning, Large Language Model (LLM), Retrieval-Augmented Generation (RAG), and MLOps solutions that power the platform.
Operating at the intersection of AI innovation and enterprise financial technology, this role works closely with product managers, solution architects, and software engineering teams to turn complex financial data and AI capabilities into scalable, secure, and reliable platform services. The Senior ML Engineer builds AI pipelines, enforces model evaluation frameworks, ensures strict security and audit compliance for regulated banking environments, and creates operational runbooks for seamless platform deployment.

Core Competencies

Machine Learning & AI Engineering: Large Language Models (LLMs) | Retrieval-Augmented Generation (RAG) | Natural Language Processing (NLP) | Model Training & Fine-Tuning | Semantic Search
MLOps & Platform Operations: Model Evaluation & Benchmarking | AI Pipeline Orchestration | Model Monitoring | Observability | Operational Runbooks | Scalable AI Deployments
Enterprise Security & Responsible AI: Data Access Controls | Audit Trails | AI Privacy & Security Compliance | Responsible AI Guardrails | Model Cards & Technical Documentation
Cross-Functional Engineering: Production Code Quality | Software Engineering Best Practices | Technical Trade-Off Communication | Cross-Functional Collaboration | AI/ML Research Integration

Technical Skills & Tools

Key Responsibilities

Design, build, and optimize production-ready Machine Learning, LLM, and RAG solutions powering the platform.
Implement advanced search, retrieval, and generative capabilities tailored to regulated financial institutions and enterprise banking workflows.
Create technical documentation, model cards, evaluation notes, implementation guidance, and operational runbooks for AI/ML features.
Build robust MLOps, evaluation, and benchmarking pipelines to continuously assess model performance, accuracy, latency, and reliability.
Stay current with modern ML, LLM, RAG, and evaluation practices, bringing practical enhancements directly into the AI platform.
Ensure all ML services adhere to strict software engineering standards, maintainability, and operational stability.
Embed enterprise-grade security, data privacy, access controls, auditability, and responsible AI guardrails into all machine learning models and pipelines.
Ensure AI capabilities satisfy regulatory compliance requirements for Tier-1 financial institutions.
Communicate technical trade-offs, model behavior, evaluation metrics, and implementation recommendations to product managers, architects, and engineering teams.
Partner with product leadership to evaluate new AI use cases, validate technical feasibility, and align ML capabilities with the product roadmap.

Required Skills

Senior-level experience designing, building, and deploying ML, LLM, or NLP systems in production environments.
Bachelor’s degree in Computer Science, Engineering, Machine Learning, Statistics, Mathematics, or a related technical field (or equivalent practical experience).
Demonstrated expertise with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Natural Language Processing (NLP), and semantic search architectures.
Hands-on experience with modern MLOps practices, model evaluation frameworks, and model benchmarking.
Deep understanding of enterprise security, data access controls, privacy, audit trails, and responsible AI practices.
Strong communication skills, with the ability to explain complex ML trade-offs and model behavior to non-technical stakeholders.

Nice to Have

Published research, open-source contributions, patents, or technical writing related to ML, NLP, search, or AI systems.
Direct experience building AI/ML platforms for financial services or regulated enterprise software environments.

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More about this job

Responsibilities

Design, build, and deploy production-grade machine learning, LLM, and RAG solutions, including search and generative capabilities for regulated financial institutions. Develop evaluation and MLOps pipelines, documentation, and operational runbooks while ensuring security, privacy, auditability, regulatory compliance, and effective collaboration with product and engineering teams.

Requirements

Requires senior-level experience deploying production ML, LLM, or NLP systems, with expertise in LLMs, RAG, NLP, semantic search, MLOps, and model evaluation. Candidates need a bachelor's degree in a relevant technical field or equivalent experience, strong knowledge of enterprise security and responsible AI, and the ability to communicate technical concepts to non-technical stakeholders.

Skills

Machine Learning
Large Language Models
Retrieval-Augmented Generation
Natural Language Processing
Semantic Search
Model Training and Fine-Tuning
MLOps
Model Evaluation and Benchmarking
AI Pipeline Orchestration
Model Monitoring
Observability
Data Access Controls
Audit Trails
Responsible AI
Enterprise Security
Technical Documentation

Visa sponsorship

Not detected in the job text

Keywords

Machine Learning
Artificial Intelligence
Large Language Models
Retrieval-Augmented Generation
Natural Language Processing
Semantic Search
Model Training
Fine-Tuning
MLOps
Model Evaluation
Benchmarking
AI Pipeline Orchestration
Model Monitoring
Observability
Operational Runbooks
Data Access Controls
Audit Trails
Data Privacy
Responsible AI
Security Compliance
Regulatory Compliance
Financial Services
Enterprise SaaS
Production Software Engineering
Technical Documentation
Model Cards
AI Platform
Scalable AI Deployments

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