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Added 6 days ago
Architect - Machine Learning
Quantiphi
Canada
Full-time
Strong proficiency in Python and experience with ML/AI frameworks such as PyTorch, TensorFlow, Scikit-learn, or Hugging Face.
Added 6 days ago
GenAI Test Engineer
J&M Group
Halifax, NS
Full-time
Build automated regression suites in Python and integrate GenAI evaluations, API tests and quality gates into CI/CD pipelines.
Added 7 days ago
Senior Quality Engineer – Test Automation, AI Testing & Java/Python
Astra-North Infoteck Inc. ~ Conquering today’s challenges, achieving tomorrow’s vision!
Toronto, ON
Full-time
Quality Engineer – Test Automation, Java/Python & GenAI
Added 6 days ago
AI / Prompt Developer – ML Engineer
Enterprise Solutions Inc.
Montreal, QC
Full-time
We are looking for an AI / Prompt Developer to join an ML/GenAI team and contribute to building and supporting AI-powered solutions.
Added 6 days ago
Lead Consultant, Gen AI
Lovelytics
Toronto, ON
Lovelytics is seeking a Lead GenAI Consultant with hands-on experience delivering client-facing projects in the Generative AI domain, particularly on the Databricks platform. As part of our…
Added 6 days ago
GenAI Developer (AWS)
Pacer Group
Toronto, ON
Contract
Hands-on expertise in Machine Learning using Python, TensorFlow, PyTorch, and Scikit-Learn.
Added 7 days ago
Co-op or Intern, Full-Stack Developer (January 2027)
BDO
Toronto, ON · Ottawa, ON · Oakville, ON
Full-time
Participate in our innovation program with exposure to GenAI (Azure OpenAI - python)
Added 7 days ago
Principal AI Engineer
Mastercard
Toronto, ON
Full-time
Experience building enterprise AI platforms, GenAI solutions, or developer platforms.
Added 6 days ago
Regression Tester
Synechron
Toronto, ON
$100,000 to $110,000 CAD / year
Full-time
…maintain automated test scripts using Selenium, Playwright, Python, and JavaScript. Lead regression testing, execute test plans, identify defects, and ensure high-quality…
Added 7 days ago
AI Deployment & Solutions Lead
Tata Consultancy Services
Toronto, ON
$115,000 to $165,000 CAD / year
Full-time
…solving complex problems by combining software engineering, AI/GenAI, data, cloud, integration and platform…
Added 12 days ago
Generative AI Engineer
PrecisionERP / PrecisionIT
Toronto, ON
Contract
Build enterprise GenAI applications using LLMs, RAG, embeddings, vector search, and AI agents.
Added 12 days ago
Python Developer
Talenzaa
Mississauga, ON
Full-time
Core Language: Strong expertise in Python (Object-Oriented Programming, clean code principles, and asynchronous programming).
Added 12 days ago
AI Benchmark Engineer | Native Language Specialist - French (Canada) - Remote
LILT
Remote, Canada
Contract · Remote
Technical Stack: Strong proficiency in Python, standard shell scripting, and data processing.
Added 12 days ago
Développeur/Développeuse GenAI / IA Générative | GenAI / Generative AI Developer
Cossette
Montreal, QC
Full-time
Solides compétences en Python dans un contexte ML/AI, et bonne maîtrise de JavaScript / TypeScript pour l'intégration et le déploiement web.
Added 12 days ago
Machine Learning Developer Associate / Développeur(euse) en apprentissage automatique associé(e)
IBM
Montreal, QC
$91,375 to $129,000 CAD / year
Full-time
As a Machine Learning Developer Associate, you will have the opportunity to work with industry-leading machine learning technologies on cloud platforms such as IBM Cloud, Microsoft Azure,…
Added 12 days ago
Machine Learning Developer Associate / Développeur(euse) en apprentissage automatique associé(e)
IBM
Toronto, ON
$91,375 to $129,000 CAD / year
Full-time
As a Machine Learning Developer Associate, you will have the opportunity to work with industry-leading machine learning technologies on cloud platforms such as IBM Cloud, Microsoft Azure,…
Added 12 days ago
AI & Automation Data Scientist Associate / Data Scientist associé(e) en IA et automatisation
IBM
Montreal, QC
$91,375 to $129,000 CAD / year
Full-time
Experience with one or more programming languages, preferably Python
Added 12 days ago
AI & Automation Data Scientist Associate / Data Scientist associé(e) en IA et automatisation
IBM
Toronto, ON
$91,375 to $129,000 CAD / year
Full-time
Experience with one or more programming languages, preferably Python
Added 12 days ago
Machine Learning Developer Associate / Développeur(euse) en apprentissage automatique associé(e)
IBM
Calgary, AB
$91,375 to $129,000 CAD / year
Full-time
As a Machine Learning Developer Associate, you will have the opportunity to work with industry-leading machine learning technologies on cloud platforms such as IBM Cloud, Microsoft Azure,…
Added 12 days ago
AI & Automation Data Scientist Associate / Data Scientist associé(e) en IA et automatisation
IBM
Calgary, AB
$91,375 to $129,000 CAD / year
Full-time
Experience with one or more programming languages, preferably Python
Added 12 days ago
Senior AI Engineer
CI Financial
Toronto, ON
Full-time
You'll be building the agents and GenAI systems that CI's advisors, analysts, and operations teams actually rely on day to day - not prototypes that stall out after the demo.
Added 16 days ago
Python Engineer- AI
Procom
Mississauga, ON
$60 to $75 CAD / hour
Contract
On behalf of our client in the financial services sector, Procom is searching for a Python Engineer for a contract-to-hire role. This position is hybrid (3 days onsite) in Mississauga,…
Added 26 days ago
PYTHON DEVELOPER - GENAI / AI
SIDRAM TECHNOLOGIES
Mississauga, ON
Full-time
Looking for a Python Developer with strong expertise in Generative AI, LLMs, RAG, Agentic AI, Data Engineering, and MLOps to build and deploy enterprise-grade AI solutions.
Added 26 days ago
PYTHON DEVELOPER - GENAI / LLM
SIDRAM TECHNOLOGIES
Mississauga, ON
Full-time
GenAI Integration with Enterprise Applications
Added 17 days ago
Quality Assurance Engineer
Paymentus
Richmond Hill, ON
$70,000 to $100,000 CAD / year
Full-time
Proficient in Java, JavaScript, or Python, as well as SQL.

Quantiphi

Architect - Machine Learning

Canada

Job type: Full-time
Posting language: English
Posted: Sep 14, 2026

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Original job description

About Quantiphi:

Quantiphi is an award-winning, AI-First global digital engineering company that helps the world’s leading Fortune 1000 organizations transform bold ideas into measurable business impact. We go beyond building innovative AI technologies - we solve the problems that matter most to our clients.

Since our founding in 2013, Quantiphi has built a proven track record of turning complex challenges into meaningful outcomes across industries.

Headquartered in Boston, with more than 4,000 professionals worldwide, we partner with global enterprises to deliver large-scale digital, cloud, and AI-driven transformation. #SolvingWhatMatters

We are an Elite and Premier partner to Google Cloud, AWS, NVIDIA, Snowflake, and other leading technology platforms, and our work has been recognized across the industry, including:

21 Google Cloud Partner of the Year awards in the past 10 years
3 AWS AI/ML Partner of the Year awards
3 NVIDIA Partner of the Year awards
3 Snowflake Partner of the Year awards
Rated Leaders by Gartner, Forrester, IDC, ISG, Everest Group and other leading analyst firms

Quantiphi delivers First-in-class AI solutions across Life Sciences, Healthcare, Banking, Financial Services, CPG, Manufacturing, Energy, High-Tech, Telecommunications, etc., powered by cutting-edge Generative AI and Agentic AI accelerators.

We are also proud to be certified as a Great Place to Work - reflecting our commitment to our people and our culture.

For more details, visit: Website or LinkedIn Page

Job Description:

Required Skills:

8+ years of experience in Machine Learning, AI, Software Engineering, Data Science, or Solution Architecture.
Strong experience designing and implementing enterprise-scale AI/ML architectures.
3+ years of hands-on experience with Generative AI, LLMs, and production AI applications.
Strong expertise in RAG (Retrieval-Augmented Generation), embeddings, vector databases, semantic/hybrid search, and knowledge retrieval.
Hands-on experience with Agentic AI, AI agents, tool/function calling, orchestration, and multi-agent workflows.
Strong proficiency in Python and experience with ML/AI frameworks such as PyTorch, TensorFlow, Scikit-learn, or Hugging Face.
Experience with LLM platforms/models such as Azure OpenAI, OpenAI, AWS Bedrock, Anthropic, Google Gemini, Llama, or equivalent.
Strong knowledge of prompt engineering, context engineering, fine-tuning, model evaluation, guardrails, and hallucination mitigation.
Experience designing and implementing MLOps/LLMOps pipelines, including model deployment, monitoring, evaluation, versioning, and CI/CD.
Strong experience with at least one major cloud platform: Microsoft Azure, AWS, or GCP.
Experience with cloud AI/ML services such as Azure Machine Learning, Azure AI Foundry, AWS SageMaker/Bedrock, or Google Vertex AI.
Experience with Docker, Kubernetes, APIs, microservices, CI/CD, and Infrastructure as Code.
Strong understanding of data pipelines, data lakes/lakehouses, databases, data governance, and enterprise integration.
Experience with AI/ML security, privacy, Responsible AI, governance, and compliance.
Strong system-design and architecture skills, with the ability to translate business requirements into scalable technical solutions.
Excellent communication, presentation, stakeholder-management, and technical leadership skills.

Key Responsibilities:

Design end-to-end enterprise AI/ML architectures from data ingestion through model development, deployment, inference, monitoring, and optimization.
Lead the architecture and implementation of Generative AI and LLM-based solutions across enterprise use cases.
Design scalable RAG architectures, including document ingestion, chunking, embeddings, vector search, retrieval, reranking, and LLM generation.
Architect and implement Agentic AI solutions, including AI agents, tool calling, workflow orchestration, memory, and human-in-the-loop capabilities.
Evaluate and recommend LLMs, AI platforms, frameworks, and technologies based on performance, scalability, security, latency, and cost.
Define architecture standards and reusable patterns for GenAI, ML, MLOps, and LLMOps.
Lead the transition of AI/ML POCs and prototypes into production-grade solutions.
Design and implement MLOps/LLMOps capabilities for model lifecycle management, deployment, monitoring, evaluation, and continuous improvement.
Establish LLM evaluation and observability frameworks covering accuracy, relevance, hallucination, latency, token usage, cost, and reliability.
Work closely with Data Scientists, ML Engineers, Software Engineers, Data Engineers, Product Managers, Security teams, and business stakeholders.
Provide technical leadership and mentorship to AI/ML engineering teams.
Ensure AI solutions meet enterprise requirements for security, privacy, governance, Responsible AI, and regulatory compliance.
Identify opportunities to improve existing AI/ML platforms and optimize performance, scalability, and cloud costs.
Create architecture diagrams, technical specifications, design documents, standards, and implementation roadmaps.
Stay current with emerging GenAI, LLM, Agentic AI, ML, and cloud technologies and assess their applicability to business needs.

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More about this job

Responsibilities

Design and implement end-to-end enterprise AI/ML architectures, focusing on Generative AI, RAG, and Agentic AI solutions. Lead the transition of prototypes into production-grade solutions while establishing evaluation and observability frameworks.

Requirements

Requires 8+ years of experience in AI/ML or Software Engineering, with at least 3 years specifically in Generative AI and LLMs. Proficiency in Python, major cloud platforms (Azure, AWS, or GCP), and MLOps pipelines is essential.

Skills

Machine Learning
Generative AI
LLMs
RAG
Agentic AI
Python
PyTorch
TensorFlow
MLOps
LLMOps
Azure OpenAI
AWS Bedrock
Google Vertex AI
Docker
Kubernetes
System Design

Visa sponsorship

Not detected in the job text

Keywords

Machine Learning
Artificial Intelligence
Generative AI
Large Language Models
RAG
Vector Databases
Agentic AI
Python
PyTorch
TensorFlow
Hugging Face
Azure OpenAI
AWS Bedrock
Google Gemini
Llama
MLOps
LLMOps
CI/CD
Docker
Kubernetes
Microservices
Infrastructure as Code
Data Lakes
Responsible AI
System Design
Cloud Computing
Azure
AWS
GCP
Vertex AI

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