AI/ML Engineer

Location: Ontario, Canada

Work Model: 100% Remote

Onsite Requirement: Occasional visits to Toronto, ON

Experience: 8+ years of overall IT experience

Employment Type: Full time

Position Overview

We are looking for an experienced AI/ML Engineer with 7+ years of overall IT experience and strong hands-on expertise in designing, developing, deploying, and operationalizing AI and Machine Learning solutions.

The ideal candidate will have strong experience with Python, Machine Learning, Generative AI/LLMs, MLOps, cloud platforms, APIs, Docker/Kubernetes, and CI/CD . The candidate should be comfortable working across the full AI/ML lifecycle, from data preparation and model development through deployment, monitoring, optimization, and production support.

This is a fully remote position; however, candidates must be based in Ontario, Canada and be available to make occasional visits to the Toronto, ON office/client location.

Key Responsibilities

- Design, develop, and deploy scalable AI/ML solutions for enterprise applications.
- Develop production-quality machine learning models using Python and frameworks such as scikit-learn, PyTorch, and/or TensorFlow .
- Build end-to-end ML pipelines covering data ingestion, preprocessing, feature engineering, model training, validation, deployment, monitoring, and retraining .
- Develop and implement Generative AI, LLM, RAG, and AI-agent solutions where applicable.
- Work with LLMs, embeddings, vector databases, prompt engineering, and model orchestration frameworks.
- Build and expose AI/ML capabilities through REST APIs and microservices .
- Implement MLOps practices including model versioning, experiment tracking, CI/CD, automated testing, deployment, monitoring, and model governance .
- Deploy and manage AI/ML workloads across Azure and/or AWS cloud environments.
- Work with services such as Azure Machine Learning, Azure OpenAI, Azure AI services, AWS SageMaker, AWS Bedrock , or equivalent platforms.
- Containerize applications and ML workloads using Docker and deploy them using Kubernetes/AKS/EKS where required.
- Build automated CI/CD pipelines using tools such as Azure DevOps, GitHub Actions, Jenkins, or similar technologies .




- Collaborate with Data Engineers to develop reliable data pipelines supporting model training and inference.
- Work with structured and unstructured data using SQL, NoSQL, data lakes, and cloud data platforms .
- Implement model performance monitoring, drift detection, logging, alerting, and automated retraining strategies.
- Apply security, privacy, responsible AI, and governance principles to enterprise AI solutions.
- Troubleshoot production AI/ML applications and resolve performance, scalability, and reliability issues.
- Collaborate with software engineers, data scientists, data engineers, DevOps teams, architects, and business stakeholders.
- Participate in technical design discussions and provide recommendations on AI/ML architecture and technology selection.
- Document technical designs, implementation approaches, deployment procedures, and operational processes.

Required Skills & Qualifications
- 7+ years of overall IT experience , with significant hands-on experience in AI/ML engineering, software engineering, data science, or related areas.
- Strong proficiency in Python .
- Strong understanding of Machine Learning algorithms, model development, evaluation, feature engineering, and optimization .
- Hands-on experience with one or more ML frameworks:
- PyTorch
- TensorFlow
- scikit-learn
- XGBoost
- Strong experience building and deploying production-grade ML solutions .
- Hands-on experience with MLOps and ML lifecycle management .
- Experience with MLflow, Kubeflow, Airflow, or equivalent MLOps/orchestration platforms .
- Strong experience with Generative AI / LLMs / RAG / Prompt Engineering .
- Experience with vector databases such as Pinecone, FAISS, Milvus, pgvector, or equivalent is an asset.
- Experience developing REST APIs and microservices using technologies such as FastAPI, Flask, or similar.
- Strong understanding of Docker and Kubernetes .
- Experience with AWS and/or Azure cloud platforms.
- Experience with cloud AI/ML services such as:




- Azure Machine Learning
- Azure OpenAI / Azure AI
- AWS SageMaker
- AWS Bedrock
- Robust understanding of CI/CD and DevOps practices .
- Experience with Git, GitHub/GitLab/Bitbucket, Jenkins, Azure DevOps, or GitHub Actions .
- Strong SQL skills and experience working with relational and/or NoSQL databases.
- Experience working with large-scale data processing platforms such as Spark/Databricks is an asset.
- Strong troubleshooting, analytical, and problem-solving skills.
- Excellent communication and collaboration skills.

Preferred / Nice-to-Have
- Experience with Agentic AI / AI Agents and frameworks such as LangChain, LangGraph, CrewAI, or AutoGen.
- Experience with RAG architecture, embeddings, vector search, and semantic search .
- Experience with Azure AI Foundry, AWS Bedrock, or Google Vertex AI .
- Experience with Kubernetes-based ML platforms and GPU workloads.
- Experience implementing model monitoring, drift detection, explainability, and responsible AI .
- Experience with Terraform or other Infrastructure as Code technologies.
- Experience working in Agile/Scrum environments.
- Cloud or AI/ML certifications such as Azure AI Engineer, AWS Machine Learning, AWS Solutions Architect, Google Professional ML Engineer, or Databricks certifications .

Candidate Location Requirement

IMPORTANT:

- Candidates must currently reside in Ontario, Canada .
- Candidates from outside Ontario will not be considered .
- This is a 100% remote position within Ontario .
- The selected candidate must be available for occasional onsite visits to Toronto, Ontario .
- Candidates must have valid authorization to work in Canada.

Education Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, Artificial Intelligence, Mathematics, or a related field , or equivalent professional experience.

Ideal Candidate The ideal candidate is a hands-on AI/ML Engineer who combines strong software engineering fundamentals with practical experience delivering ML, GenAI, and MLOps solutions into production . They should be comfortable working across AI development, cloud infrastructure, deployment automation, monitoring, and enterprise integration rather than focusing exclusively on model development.

📌 AI/ML Engineer (Ontario)
🏢 Carbonsoft
📍 Ontario