Jobs in Canada

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Added 21 days ago
HT
Software Validation Technologist
Husky Technologies
Bolton, ON
- Full-time
Implement software validation engineering test plans, cases plus scripts.
Added 21 days ago
NOC Specialist
Rogers Communications
Calgary, AB · Burnaby, BC · North Vancouver, BC · Vancouver, BC · BC · West Vancouver, BC
CCNA or CCNP Routing & Switching certification required; Service Provider certification is considered an asset
Added 21 days ago
T
Data Scientist - Credit Risk (ATH 5531)
TD
Toronto, ON
- Full-time
Use data, analytics, and business insight to identify opportunities, improve credit strategies and customer outcomes, and answer not just "what happened?", but "so what?" and "what should…
Added 21 days ago
BR
Robotics Software Developer – ROS2, State Estimation, Perception
BHF Robotics
Markham, ON
- Full-time
Development Skills: Exceptional C++ / Python programming skills with a strong grasp of modern software engineering practices (Git, CI/CD, unit testing, profiling).
Added 21 days ago
C
Senior AI Engineer
Cloudoplus
ON · Ontario, Canada
- Full-time
…accomplished Senior AI Engineer with 10+ years of enterprise software engineering, machine learning, artificial intelligence, and distributed systems experience to architect, design,…
Added 21 days ago
P
Lead Data Scientist, Innovation Lab
PakEnergy
Calgary, AB
- Full-time
…customer pilots, and for the ML models you own, define the data, monitoring and MLOps requirements for a clean handoff to product and engineering…
Added 21 days ago
CA
Manager – Data Engineering & Platforms
Canadian Addiction Treatment Centers
Markham, ON
- $125,000 to $150,000 CAD / year
- Full-time
…healthcare services across Canada. CATC is is seeking a Manager, Data Engineering & Platforms to lead the development, operation and continuous improvement of CATC's enterprise data…
Added 21 days ago
Q
Machine Learning Engineer, AI Processors
Qualcomm
Markham, ON
- Full-time
Engineering Group, Engineering Group > Machine Learning Engineering
Added 21 days ago
Q
Staff Machine Learning Framework, Complier & Performance Engineer
Qualcomm
Canada
- Full-time
Engineering Group, Engineering Group > Machine Learning Engineering
Added 21 days ago
SM
RQ11486 – Data Ops/Cloud Data Engineer – Senior
S M Software Solutions Inc
Toronto, ON
- Internship
Work Arrangement: Onsite – 5 Days per Week · Candidates Must Demonstrate Strong Hands-on Experience In The Mandatory Technical Skills And Responsibilities Outlined In The Must Have And General
Added 21 days ago
SM
RQ11486 – Data Ops/Cloud Data Engineer – Senior
S M Software Solutions Inc
Toronto, ON
- Internship
Work Arrangement: Onsite – 5 Days per Week · Candidates Must Demonstrate Strong Hands-on Experience In The Mandatory Technical Skills And Responsibilities Outlined In The Must Have And General
Added 21 days ago
SM
RQ11486 – Data Ops/Cloud Data Engineer – Senior
S M Software Solutions Inc
Toronto, ON
- Internship
Work Arrangement: Onsite – 5 Days per Week · Candidates Must Demonstrate Strong Hands-on Experience In The Mandatory Technical Skills And Responsibilities Outlined In The Must Have And General
Added 21 days ago
SM
Python Developer - Hybrid
S M Software Solutions Inc
Mississauga, ON
- Full-time
The Python Developer will develop software solutions using Python, applying strong software engineering principles and data manipulation techniques. The role involves analyzing source code…
Added 21 days ago
SM
Python Developer - Hybrid
S M Software Solutions Inc
Mississauga, ON
- Full-time
The Python Developer will develop software solutions using Python, applying strong software engineering principles and data manipulation techniques. The role involves analyzing source code…
Added 21 days ago
ZC
Machine Learning Engineer
Zurich Canada
Toronto, ON
- Full-time
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…
Added 21 days ago
ZC
Machine Learning Engineer
Zurich Canada
Waterloo, ON
- Full-time
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…
Added 21 days ago
SM
Python Developer
S M Software Solutions Inc
Mississauga, ON
- Full-time
This is an on-site assignment, requiring candidates to be present in the office five days per week
Added 21 days ago
C
Ingénieur(e) applications GenAI / agentiques et DevSecOps
CGI
Montreal, QC
- Full-time
Build data pipelines for RAG: ingestion, chunking, embeddings, vector indexing, hybrid search and reranking.
Added 21 days ago
SM
Python Developer - Hybrid
S M Software Solutions Inc
Mississauga, ON
- Full-time
The Python Developer will develop software solutions using Python, applying strong software engineering principles and data manipulation techniques. The role involves analyzing source code…
Added 21 days ago
SM
Python Developer
S M Software Solutions Inc
Mississauga, ON
- Full-time
This is an on-site assignment, requiring candidates to be present in the office five days per week
Added 21 days ago
SM
Python Developer
S M Software Solutions Inc
Mississauga, ON
- Full-time
This is an on-site assignment, requiring candidates to be present in the office five days per week
Added 21 days ago
C
Senior Enterprise Architecture Consultant – Enterprise Modernization
CGI
Vancouver, BC
- Full-time
Guide Python based matching services and related data processing, validation, and stewardship patterns.
Added 21 days ago
GF
Electrical Engineer (Controls and Infrastructure)
General Fusion Inc
Richmond, BC
- $100,000 to $140,000 CAD / year
Bachelor's degree in Electrical Engineering or equivalent, and registration (or eligibility for registration) as a Professional Engineer (P.Eng.) with EGBC.
Added 21 days ago
AW
Data Engineer, Temporary
Aviso Wealth
Remote, Canada
- Temporary
- Remote
Reporting to the Sr Director, Data Platform Delivery and Engineering, the Data Engineer is responsible for designing, building, and collaborating with Development, Security, and TSP Ops…
Added 21 days ago
AW
Data Engineer, Temporary
Aviso Wealth
Remote, Canada
- Temporary
- Remote
Reporting to the Sr Director, Data Platform Delivery and Engineering, the Data Engineer is responsible for designing, building, and collaborating with Development, Security, and TSP Ops…

Cloudoplus

Senior AI Engineer

ON, Canada
Ontario, Canada, Canada

Full-time

Apply on LinkedIn About employer

Applications open in a new tab.

Job details

Job type: Full-time
Apply by: Apr 18, 2027
Posting language: English
Posted: Oct 20, 2026

Original job description

We are seeking a highly experienced and technically accomplished Senior AI Engineer with 10+ years of enterprise software engineering, machine learning, artificial intelligence, and distributed systems experience to architect, design, develop, and deploy highly scalable, production-grade AI platforms.

The ideal candidate will possess deep expertise in Large Language Models (LLMs), Generative AI, Agentic AI, deep learning, transformer architectures, Retrieval-Augmented Generation (RAG), multi-agent orchestration, AI reasoning systems, and cloud-native AI infrastructure.

This position requires extensive hands-on experience developing sophisticated AI applications, optimizing foundation models, implementing autonomous agent workflows, and integrating intelligent systems with complex enterprise platforms.

Key Responsibilities

1. Advanced AI Architecture and Foundation Model Engineering

Architect and implement enterprise-grade artificial intelligence platforms utilizing advanced machine learning algorithms, deep neural networks, transformer architectures, and distributed model-serving infrastructure.

Implement and optimize attention mechanisms, including Multi-Head Attention (MHA), Multi-Query Attention (MQA), Grouped-Query Attention (GQA), FlashAttention, and Rotary Positional Embeddings (RoPE).

Develop custom neural network architectures utilizing PyTorch, TensorFlow, JAX, Hugging Face Transformers, and distributed training frameworks.

Implement advanced model adaptation techniques including supervised fine-tuning (SFT), LoRA, QLoRA, parameter-efficient fine-tuning (PEFT), knowledge distillation, and domain-adaptive training.

Optimize model inference performance using quantization, speculative decoding, KV-cache optimization, continuous batching, tensor parallelism, and pipeline parallelism.

Evaluate and integrate commercial and open-weight foundation models, including GPT, Claude, Gemini, Llama, Qwen, Mistral, and Gemma, based on application requirements, latency, throughput, accuracy, and cost.

2. Generative AI and Advanced LLM Application Development

Design and develop sophisticated Generative AI applications utilizing large language models, multimodal foundation models, and advanced prompt engineering techniques.

Implement structured generation, constrained decoding, function calling, tool execution, and schema-based output validation for reliable enterprise AI applications.

Develop advanced reasoning workflows utilizing planning, decomposition, reflection, self-correction, and iterative verification mechanisms.

Engineer context-management strategies involving semantic compression, dynamic context assembly, prompt caching, and long-context optimization.

Implement enterprise-grade LLM evaluation frameworks to measure factual accuracy, reasoning performance, groundedness, hallucination rates, toxicity, latency, and token utilization.

3. Agentic AI and Autonomous Multi-Agent Systems

Architect and implement advanced Agentic AI platforms capable of autonomous task planning, dynamic decision-making, tool execution, and complex workflow orchestration.

Develop multi-agent systems utilizing LangGraph, LangChain, CrewAI, AutoGen, Semantic Kernel, and custom Python-based orchestration frameworks.

Design and develop agent memory architectures incorporating short-term conversational memory, persistent long-term memory, semantic memory, episodic memory, and structured state management.

Integrate Model Context Protocol (MCP) clients and servers to securely expose enterprise tools, APIs, databases, and business services to AI agents.

Develop secure agentic transaction workflows utilizing Temporal, Saga orchestration, idempotency, transactional outbox patterns, and compensating transactions..

4. Retrieval-Augmented Generation (RAG) and Enterprise Knowledge Systems

Architect advanced Retrieval-Augmented Generation platforms integrating structured, semi-structured, and unstructured enterprise knowledge sources.

Implement hybrid retrieval architectures combining dense vector embeddings, sparse retrieval, BM25, semantic search, and metadata-based filtering.

Develop multi-stage retrieval pipelines incorporating query rewriting, query decomposition, reranking, contextual retrieval, and relevance optimization.

Design Graph RAG architectures integrating knowledge graphs, graph databases, entity resolution, relationship extraction, and graph traversal.

Implement vector search solutions using Pinecone, Milvus, Weaviate, FAISS, Elasticsearch, OpenSearch, and PostgreSQL with pgvector.

Develop enterprise document intelligence pipelines incorporating document parsing, OCR, semantic chunking, hierarchical indexing, and contextual metadata enrichment.

Implement knowledge ingestion and synchronization pipelines supporting incremental updates, change data capture, data lineage, access controls, and document versioning.

Evaluate retrieval quality using Recall@K, Precision@K, Mean Reciprocal Rank (MRR), NDCG, answer relevance, faithfulness, and citation correctness.

5. Machine Learning, Deep Learning, and Predictive AI

Design and implement advanced supervised, unsupervised, self-supervised, and reinforcement learning solutions for complex enterprise use cases.

Develop predictive modeling pipelines utilizing XGBoost, LightGBM, Random Forest, Support Vector Machines, gradient boosting, and deep neural networks.

Implement distributed model training and experimentation using PyTorch Distributed, DeepSpeed, Ray Train, and distributed data-processing frameworks.

Apply explainable AI methodologies including SHAP, LIME, feature attribution, model interpretability, and model fairness analysis.

Establish rigorous model-validation practices including cross-validation, drift analysis, calibration, robustness testing, and out-of-distribution evaluation.

6. Cloud AI Platforms and Infrastructure Engineering

Design cloud-native AI solutions utilizing Amazon Bedrock, Amazon SageMaker, Azure AI Foundry, Azure Machine Learning, Google Vertex AI, and managed foundation model services.

Implement GPU-accelerated computing environments utilizing NVIDIA CUDA, cuDNN, NCCL, and distributed GPU clusters..ip

Required Qualifications

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, or a closely related technical discipline.

10+ years of professional experience in software engineering, distributed systems, data engineering, machine learning, or artificial intelligence, including substantial recent hands-on experience delivering production AI solutions.

Advanced proficiency in Python, object-oriented programming, asynchronous programming, data structures, algorithms, and distributed application development.

Strong experience with PyTorch, TensorFlow, Hugging Face Transformers, scikit-learn, and modern machine learning frameworks.

Demonstrated expertise in developing Generative AI applications, LLM-powered solutions, RAG architectures, and autonomous agent workflows.

Extensive experience with cloud computing, container orchestration, microservices architecture, distributed messaging, and production AI infrastructure.

Strong understanding of transformer architectures, neural network optimization, vector databases, embedding models, and advanced information retrieval.

Proven ability to design and implement secure, scalable, fault-tolerant enterprise AI systems.

Excellent analytical, architectural, troubleshooting, technical leadership, and communication skills.

Apply on LinkedIn About employer

More about this job

Responsibilities

Architect, develop, and deploy scalable enterprise AI platforms and applications, including foundation models, generative AI, autonomous agents, and retrieval-augmented generation systems. Optimize model training and inference, build secure knowledge and data pipelines, and deliver production AI infrastructure across cloud and distributed computing environments.

Requirements

Requires a bachelor's or master's degree in a relevant technical discipline and 10+ years of experience in software engineering, distributed systems, data engineering, machine learning, or artificial intelligence, including recent hands-on production AI work. Candidates should have advanced Python and machine learning framework skills, expertise in LLMs, RAG, and agent workflows, and experience building secure, scalable enterprise systems on cloud infrastructure.

Skills

Python
PyTorch
TensorFlow
Hugging Face Transformers
Generative AI
Large Language Models
Retrieval-Augmented Generation
Agentic AI
Distributed Systems
Machine Learning
Deep Learning
Cloud Computing
Vector Databases
Multi-Agent Orchestration
Model Optimization
Enterprise AI Architecture

Visa sponsorship

Not detected in the job text

Keywords

Python
PyTorch
TensorFlow
JAX
Hugging Face Transformers
Large Language Models
Generative AI
Agentic AI
Retrieval-Augmented Generation
Transformer Architectures
LoRA
QLoRA
Parameter-Efficient Fine-Tuning
LangGraph
LangChain
CrewAI
AutoGen
Semantic Kernel
Model Context Protocol
Pinecone
Milvus
Weaviate
FAISS
PostgreSQL
pgvector
Amazon Bedrock
Amazon SageMaker
Azure AI Foundry
Google Vertex AI
NVIDIA CUDA

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Jobs in Canada