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Data Engineer – Computer Vision & Backend Infrastructure

Latii

Markham

On-site

CAD 70,000 - 110,000

Full time

7 days ago
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Job summary

A leading AI company seeks a Data Engineer to enhance their computer vision capabilities. This entry-level position involves developing data pipelines and deploying machine learning models using Python and related tools, in a collaborative and innovative environment. The role offers a unique opportunity to impact the efficiency of the window and door industry's quoting process and is based in Markham, Ontario.

Qualifications

  • Proficiency in Python for data processing and backend development.
  • Experience with PyTorch and deploying machine learning models.
  • Familiarity with Docker and REST APIs for backend services.

Responsibilities

  • Develop and manage data pipelines for computer vision tasks.
  • Extend Python-based scripts for model evaluation and training.
  • Deploy models using PyTorch and serve with FastAPI.

Skills

Python
Computer Vision
Backend Development
Data Processing

Tools

PyTorch
FastAPI
Docker

Job description

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We build an AI-powered tool that automates the quoting process for window and door industry participants. Our platform ingests drawings, emails, and other quotes to generate accurate estimates in minutes, not days. By streamlining manual workflows, we help our customers and other stakeholders save time, reduce labor costs, and scale their businesses more efficiently.

About the Role:

We’re seeking a Data Engineer with strong computer vision knowledge and a solid foundation in backend development to join our AI/ML team. In this role, you’ll support the end-to-end lifecycle of computer vision models—from data ingestion and preprocessing to deployment and serving—while also helping to build and maintain the backend infrastructure that powers our AI features.

Key Responsibilities:

  • Develop and manage data pipelines for handling images used in training and inference.
  • Understand and extend Python-based computer vision scripts for preprocessing, model evaluation and model development.
  • Deploy deep learning models using PyTorch and serve them in production using FastAPI , Docker , and related tools.
  • Design and maintain backend services that integrate ML models into products, with a focus on performance, scalability, and reliability.
  • Work with ML engineers and product developers to ensure seamless integration of models into customer-facing features.

Qualifications:

  • Strong proficiency in Python , especially for data processing, computer vision tasks, and backend development.
  • Hands-on experience with PyTorch and model training workflows.
  • Proven experience building and maintaining FastAPI or similar web backends for serving machine learning models.
  • Familiarity with Docker , REST APIs, and basic DevOps practices for deploying and monitoring services.
  • Solid understanding of data structures and engineering best practices for handling large-scale visual data

Bonus Skills:

  • Experience with image annotation platforms (e.g., CVAT, Roboflow).
  • Proficiency with MLflow for experiment tracking and model versioning.
  • Experience training and deploying models using platforms like Amazon Bedrock , Databricks , or similar cloud-based ML services.
  • Knowledge of MLOps best practices and model monitoring in production environments.
  • Familiarity with cloud infrastructure (AWS, GCP) for scaling services and storage.

Other:

  • Full-time; 4-day in office (Markham, Ontario)
Seniority level
  • Seniority level
    Entry level
Employment type
  • Employment type
    Full-time
Job function
  • Job function
    Information Technology
  • Industries
    Wholesale Building Materials

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