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Added 2 months ago
AI Scientist & Engineer, Assurance Innovation Lab
BDO
London, ON · Toronto, ON · Ottawa, ON · Oakville, ON · Kitchener, ON · Markham, ON · Vancouver, BC
Full-time
We are looking for an exceptionally skilled, hands-on, and innovation-minded AI Scientist & Engineer to bridge the gap between advanced data science, experimental machine learning, and…
Added 10 days ago
Senior Machine Learning / AI Engineer
INETCO Systems Ltd.
Vancouver, BC
Full-time
We are looking for a Senior Machine Learning / AI Engineer to help design, build, test and deploy machine learning and AI-based systems for our BullzAI product line.
Added 10 days ago
Senior / Staff Software Engineer, AI Tech Strike Team
Waabi
Toronto, ON
$165,000 to $265,000 USD / year
Full-time
…including prompt engineering, evals, tool use, and integrating LLMs into production…
Added 4 months ago
Forward Deployment Engineer (Generative AI)
Tiger Analytics
Canada
Full-time
Tiger Analytics is looking for experienced Forward Deployment Engineer (Generative AI) with Gen AI experience to join our fast-growing advanced analytics consulting firm. Our employees…
Added 11 days ago
Staff Data Scientist
Purpose Unlimited
Remote, Canada
Full-time · Remote
…evolves its platform for years - and increasingly, how our AI systems understand and serve the clients who depend on…
Added 10 days ago
Lead AI Engineer
Altus Group
Toronto, ON
Full-time
…environments, valuation data, analytics, and evolving agentic systems - all within a culture that values curiosity, experimentation, continuous learning, and pragmatic problem-solving. You…
Added 11 days ago
Staff AI Engineer
Arcadia
Toronto, ON · Greater Toronto Area, Canada
$220,000 to $300,000 CAD / year
Full-time
This is not an AI research role. We're looking for a Staff-level software engineer who can define the architecture and technical direction for large-scale AI infrastructure across…
Added 11 days ago
Senior Software Engineer (Back-end/Server)
Trulioo
Vancouver, BC · Toronto, ON
Full-time
Trulioo is looking for a Senior Software Engineer to lead the architecture and development of high-throughput, low-latency back-end services that power our Document and Biometric…
Added 11 days ago
Senior AI Engineer
Mastercard
Vancouver, BC
Full-time
…Development remit. The remit builds the internal tooling and agentic systems that make AI development faster and more repeatable across Mastercard and works alongside data science teams to…
Added 2 months ago
Applied AI, Forward Deployed Machine Learning Engineer - Montreal
Mistral
Montreal, Quebec
Full-time
You have deep understanding of concepts and algorithms underlying machine learning and LLMs
Added 5 months ago
Engineer – ML & RL
Huawei Canada
Edmonton, Alberta
Full-time
Design and build scalable infrastructure to support Reinforcement Learning, Online Search, Recommendation Systems, large model fine-tuning and evaluation/deployment.
Added 2 months ago
{NEW} Applied AI, Technical Lead, Forward Deployed AI Engineer
Mistral
Montreal, Quebec
Full-time
- You hold a PhD or Master’s degree in AI, Machine Learning, Computer Science, or a related field.
Added 12 days ago
Innovation, Data & Analytics Team, Senior Data Scientist (AI Lead)
Pfizer
Montreal, QC
Full-time
Hands-on experience evaluating and experimenting with LLMs and agentic systems
Added 12 days ago
Generative AI Data Scientist & ML Engineer
Royal Bank of Canada
Toronto, ON
Full-time
Collaborative Research: Collaborate with other data scientists, machine learning engineers, and domain experts to identify new opportunities for applying LLMs and AI agents, and contribute…
Added 12 days ago
Data Scientist and AI Engineer Autonomous AI Agents (LLMs and Deep Learning)
Royal Bank of Canada
Toronto, ON
Full-time
…AI agents that leverage and fine-tune large language models (LLMs) and other deep learning models. As an AI Engineer, you will play a pivotal role in building intelligent systems that…
Added 12 days ago
Generative AI Data Scientist & ML Engineer
RBC
Toronto, ON
Full-time
Collaborative Research: Collaborate with other data scientists, machine learning engineers, and domain experts to identify new opportunities for applying LLMs and AI agents, and contribute…
Added 12 days ago
Data Scientist and AI Engineer Autonomous AI Agents (LLMs and Deep Learning)
RBC
Toronto, ON
Full-time
…AI agents that leverage and fine-tune large language models (LLMs) and other deep learning models. As an AI Engineer, you will play a pivotal role in building intelligent systems that…
Added 2 months ago
Machine Learning Engineer , Amazon Customer Service
Amazon
Vancouver, British Columbia
We are looking for a Machine Learning Engineer on the Data Intelligence team which is part of Amazon Customer Service (CS) team, you will design and build robust, scalable AI/ML systems and…
Added 3 months ago
Senior AI Engineer
iManage
Toronto, Ontario
Full-time
You are passionate about building and deploying AI systems that work at scale in production. You will work within the Applied AI team alongside engineers, data scientists, and product…
Added 3 months ago
Computer Vision/ML Engineer
Norbert Health
Montreal, Quebec
Full-time
We are looking for our lead deep learning engineer to spearhead the development of our groundbreaking sensing technology.
Added 3 months ago
Research Engineer – Multimodal AI & Interaction
Huawei Technologies Canada Co., Ltd.
Markham, ON
Full-time
The Huawei Human-Machine Interaction Lab unites global researchers, engineers, and designers to redefine human technology relationships through user centered, hands on research. We focus on…
Added 3 months ago
Senior AI Engineer
iManage
Toronto, Ontario
Full-time
You are passionate about building and deploying AI systems that work at scale in production. You will work within the Applied AI team alongside engineers, data scientists, and product…
Added 3 months ago
AI and Data Engineer
Blend360
Edmonton, Alberta
Full-time
Familiarity with LLMs and modern AI tooling: prompt engineering, fine-tuning, RAG pipelines, orand agent frameworks (LangChain, LangGraph LlamaIndex, CrewAI, or equivalent)
Added 3 months ago
Co-op Engineer - AI Software Engineering
Huawei Technologies Canada Co., Ltd.
Markham, ON
Internship
AI & ML Integration: Working knowledge of Machine Learning principles and Large Language Models (LLMs) applied to software engineering workflows.
Added 3 months ago
Senior Data Scientist | Scientifique de données senior
Jesta I.S.
Westmount, Quebec · Montreal, Quebec
Full-time
…enterprise applications that combine predictive analytics, machine learning, generative AI, agentic AI, and computer vision directly within business workflows. Our AI Centre of Excellence…

Amazon

Machine Learning Engineer , Amazon Customer Service

Vancouver, BC, Canada

Experience: 3+ years of contributing to new and current systems architecture and design (architecture, design patterns, reliability and scaling) experience
Posting language: English
Posted: Jun 26, 2026

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Original job description

We are looking for a Machine Learning Engineer on the Data Intelligence team which is part of Amazon Customer Service (CS) team, you will design and build robust, scalable AI/ML systems and infrastructure. You'll architect end-to-end AI pipelines for model training, evaluation, and deployment, implement secure and efficient data processing solutions, and develop production-grade AI services including generative AI, large language models (LLMs), and intelligent agent systems. Additionally, you'll build infrastructure that supports the complete lifecycle of AI models - from experimentation and development to production deployment and monitoring.

You'll work with cross-functional teams (e.g., scientists, product managers, data engineers) to create enterprise-scale AI/ML systems that handle high-volume inference workloads, implement comprehensive model and AI governance frameworks, and build scalable AI-powered products that power critical business capabilities.

If you enjoy solving complex AI and machine learning challenges in high-scale environments, working in a collaborative and dynamic team, and want to make a lasting impact on Amazon Customer Service worldwide, this is your opportunity. Come join us on this exciting journey!

Key job responsibilities
- Design and implement enterprise-scale AI/ML pipelines and model serving infrastructure that ensure optimal performance, reliability, and low-latency inference for both traditional ML models and generative AI systems.
- Architect and build AI platform infrastructure that supports the complete model lifecycle, from training environments, feature stores, and validation frameworks to production deployment, A/B testing, and monitoring systems.
- Develop and deploy generative AI solutions, including LLM-based applications, retrieval-augmented generation (RAG) systems, AI agents, and intelligent automation workflows.
- Build and optimize AI model serving systems for production use, including model compression, quantization, prompt engineering pipelines, and efficient serving strategies to meet latency and throughput requirements.
- Develop and maintain robust AI governance frameworks, implementing security controls, guardrails, responsible AI practices, and compliant data access patterns that protect sensitive information.
- Drive technical architecture decisions and system design, focusing on scalability, reliability, and performance of distributed AI/ML services while ensuring alignment with business requirements.
- Own end-to-end delivery of AI/ML solutions, including design, implementation, experimentation, and verification of components, using standard software engineering and AI/ML engineering methodologies and best practices.
- Collaborate with cross-functional teams, including Product Managers, Applied Scientists, and Data Engineers, to understand requirements, conduct design reviews, and ensure successful delivery of AI solutions while maintaining high development standards.

A day in the life
A typical day as a Machine Learning Engineer involves architecting and building robust AI/ML infrastructure and intelligent systems that power critical AI initiatives. Your morning might start with reviewing model performance metrics and experiment results, collaborating with Applied Scientists to optimize LLM prompting strategies or model architectures, or working with Product Managers to plan AI product features.

Throughout the day, you'll write and review code for AI/ML pipelines, generative AI applications, and model serving systems, while monitoring and optimizing existing AI services for performance, accuracy, and reliability. You'll often find yourself diving deep into model behavior issues, implementing guardrails for responsible AI deployment, improving inference latency and throughput, and building new capabilities into our AI platforms. Cross-team collaboration is key, as you work closely with scientists to translate innovative AI research into production-ready systems and consult with data engineers to ensure high-quality feature and knowledge pipelines. As a senior member of the team, you'll also mentor junior engineers, sharing your expertise in AI system design and best practices.

About the team
The Data Intelligence team is a new function within Customer Engagement Technology. We own the end-to-end process of defining, building, implementing, and monitoring a comprehensive data and AI strategy. We also develop and apply Generative Artificial Intelligence (GenAI), Large Language Models (LLMs), Computer Vision, ML, Knowledge Graphs, and Natural Language Processing (NLP) to customer service associate experiences and foundational technologies. Basic Qualifications: - 3+ years of contributing to new and current systems architecture and design (architecture, design patterns, reliability and scaling) experience
- Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution
- Experience in machine learning, data mining, information retrieval, statistics or natural language processing Preferred Qualifications: - 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Master's degree in computer science or equivalent
- Experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. As a total compensation company, Amazon's package may include other elements such as sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon offers comprehensive benefits including health insurance (medical, dental, vision, prescription, basic life & AD&D insurance), Registered Retirement Savings Plan (RRSP), Deferred Profit Sharing Plan (DPSP), paid time off, and other resources to improve health and well-being. We thank all applicants for their interest, however only those interviewed will be advised as to hiring status.

CAN, BC, Vancouver - 114,800.00 - 191,800.00 CAD annually

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More about this job

Responsibilities

Design and build scalable AI/ML infrastructure and end-to-end pipelines for model training, evaluation, and deployment. Develop production-grade generative AI services and implement robust AI governance frameworks to support Amazon Customer Service.

Requirements

Requires 3+ years of experience in systems architecture and design, with a strong foundation in ML and LLM lifecycles. Preferred candidates hold a Master's degree in Computer Science and have experience deploying LLMs on AI acceleration hardware.

Skills

Machine Learning
Large Language Models
Generative AI
AI Pipeline Architecture
Model Deployment
RAG Systems
AI Agents
Model Quantization
Prompt Engineering
AI Governance
Distributed Systems
Software Engineering
Data Mining
Natural Language Processing
Statistics
Information Retrieval

Benefits

Health Insurance
Medical Insurance
Dental Insurance
Vision Insurance
Prescription Insurance
Basic Life Insurance
AD&D Insurance
Deferred Profit Sharing Plan (DPSP)
Paid Time Off

Visa sponsorship

Not detected in the job text

Keywords

Machine Learning
LLM
Generative AI
RAG
AI Agents
Model Compression
Quantization
Prompt Engineering
AI Governance
Distributed Systems
NLP
Computer Vision
Knowledge Graphs
GPU
Neuron
TPU
Feature Stores
A/B Testing
Data Intelligence
Inference Optimization
Scalability
Reliability
Low-latency Inference
Responsible AI
Data Mining
Information Retrieval
Statistics
System Design
Architecture Patterns

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