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Entry Level Computer Vision Deep Learning Engineer Jobs in L Assomption, QC

Vooban

AI scientist pre-sales

Montreal, QC · On-site

Computer vision et IoT en deuxième : contrôle qualité physique, tri visuel automatisé * Machine learning généraliste et recherche opérationnelle de façon ponctuelle, quand le contexte client ...

Unitytech

Senior Software Engineer, QA

Montreal, QC · On-site

CA$111K - CA$161K/yr

... both entry-level and high-performance devices. This will be accomplished by establishing ... Zone A: CA$103,000 - CA$153,000 CAD gross Zone B: CA$111,100 - CA$161,100 CAD gross Cette ...

Ironbelly Studios

AI Platform Engineer

Montreal, QC · Hybrid

Deep, production-level experience in Python (3.11+), building microservices with frameworks like ... Health, dental, and vision package , plus flexible PTO. * Growth & Learning: A professional ...

Mako Fintech

Solutions Engineer

Montreal, QC · Remote

This is an entry-level software development position, where you'll gain experience in Git, Agile ... Educational background in computer science, math, physics or engineering. * Basic coding and ...

Mako

Solutions Engineer

Montreal, QC · Remote

This is an entry-level software development position, where you'll gain experience in Git, Agile ... Educational background in computer science, math, physics or engineering. * Basic coding and ...

h2o.ai

Customer Support Engineer

Montreal, QC · On-site

We're leveraging MLOps to transform machine learning models from isolated, engineer-specific tools ... Bachelor's or a higher education degree in Computer Science/Engineering or related field. * Proven ...

Ubisoft

Software Engineer - MLOPS

Montreal, QC · On-site

As a Machine Learning Operations Software Engineer at Ubisoft Montréal, you will help build ... Ability to connect high level vision with technical details * Collaborative mindset with clear and ...

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All JobsComputer Vision Deep Learning Engineer JobsEntry Level Computer Vision Deep Learning Engineer JobsEntry Level Computer Vision Deep Learning Engineer Jobs in L'Assomption, QC

Entry Level Computer Vision Deep Learning Engineer information

What does an entry level computer vision deep learning engineer do?

An Entry Level Computer Vision Deep Learning Engineer works on developing and implementing algorithms that allow computers to interpret and understand visual information from the world, such as images or videos. They typically use deep learning techniques, especially neural networks, to build models for tasks like object detection, facial recognition, and image classification. Their responsibilities may include data preprocessing, model training and evaluation, writing code (often in Python), and collaborating with senior engineers on real-world projects. This role is ideal for those who have a strong foundation in machine learning, programming, and mathematics, but are just starting their careers in the field.

What types of projects do entry level computer vision deep learning engineers typically work on, and how is their work structured within a team?

As an entry-level Computer Vision Deep Learning Engineer, you can expect to contribute to projects like object detection, image classification, and model optimization for real-world applications. Your tasks may include data preprocessing, training and evaluating neural networks, and writing code to integrate models into products or pipelines. You'll often collaborate closely with senior engineers, data scientists, and product managers, typically working in agile teams where regular code reviews and knowledge sharing are common. This collaborative environment not only helps you learn best practices but also provides opportunities to gradually take on more responsibility as your skills develop.

What are the key skills and qualifications needed to thrive as an entry level computer vision deep learning engineer, and why are they important?

To thrive as an Entry Level Computer Vision Deep Learning Engineer, you need a solid understanding of computer vision fundamentals, deep learning concepts, and programming skills in languages like Python, along with a relevant degree in computer science, engineering, or a related field. Familiarity with frameworks such as TensorFlow or PyTorch, experience with OpenCV, and knowledge of version control systems like Git are typically required. Strong problem-solving abilities, attention to detail, and effective communication skills help you collaborate within teams and tackle complex challenges. These skills and qualities are crucial for developing, deploying, and optimizing computer vision solutions that meet real-world business needs.
Entry Level Computer Vision Deep Learning Engineer jobs near you
Infographic showing various Entry Level Computer Vision Deep Learning Engineer job openings in L'Assomption, QC as of June 2026, with employment types broken down into 75% Full Time, 22% Part Time, and 3% Contract. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution.

Senior Data Platform Engineer (Python) | API's, Analytics & Machine Learning | Hybrid (Montreal) | $

Montreal, QC • Hybrid

White Bay
See more jobs at White Bayexternal

$140K - $150K/yr

Full-time

Medical, Dental, Vision, PTO

Posted 16 days ago

Job description

Senior Data Platform Engineer (Python) | API’s, Analytics & Machine Learning | Hybrid (Montreal) | $140,000 - $150,000 CAD + Equity & Benefits


The Company

They make cities understandable. Not in theory, but in data. They’ve built a platform that translates the chaos of urban environments into something usable: insights that help governments, developers, and businesses make better decisions about how cities are built and evolve. Backed by serious funding and born out of academic research, they’re now operating at scale, processing massive datasets across North America and turning them into real-world applications. The mission is ambitious: better cities, built with better data. The kind that actually works for the people living in them.


The Role

This is a senior, hands-on data engineering role focused on scaling and refining a high-volume data platform. You’ll be working on systems that process tens of terabytes of geospatial and real-world data, powering APIs, analytics products, and machine learning models used by both internal teams and external customers. The platform already works. Your job is to make it faster, cleaner, and harder to break. You won’t just be building pipelines, you’ll be shaping how data moves, how it’s trusted, and how it scales as complexity grows.


The Responsibilities

  • Design, build, and operate large-scale batch data pipelines and lakehouse datasets (~30TB+)
  • Ensure data systems are reliable, cost-efficient, and consistently refreshed across daily, monthly, and quarterly cycles
  • Translate requirements from data science, product, and engineering teams into scalable data architecture
  • Establish and enforce standards around data quality, validation, lineage, and governance
  • Improve observability, monitoring, and alerting across the data platform
  • Drive best practices in software engineering, including testing, performance, and security
  • Mentor other engineers through code reviews, design input, and architectural guidance
  • Support data delivery into production systems, APIs, and downstream applications


The Requirements

  • Proven experience building and operating production-grade batch data pipelines at scale
  • Strong Python skills, with a focus on writing clean, testable, production-ready code
  • Experience working with modern data stack tools (e.g. lakehouses, orchestration frameworks, distributed processing)
  • Solid understanding of data modeling, orchestration, observability, and cost optimization
  • Experience integrating pipelines with production databases while maintaining data integrity
  • Familiarity with cloud-native environments (AWS preferred), containerization, and distributed systems
  • Experience with tools such as Spark, Dagster (or similar), and modern CI/CD workflows
  • Exposure to geospatial data or spatial analytics is a strong advantage
  • Strong communication skills and the ability to work cross-functionally
  • Comfortable operating in a fast-moving environment with evolving priorities


The Remuneration

  • $140,000 - $150,000 CAD with equity participation
  • Comprehensive health coverage (medical, dental, vision)
  • Access to mental health support, telemedicine, and employee assistance programs
  • Unlimited vacation policy with an emphasis on actual use
  • Annual health and wellness allowance
  • Remote work setup support
  • Annual professional development budget (~$1,500 CAD)
  • Additional perks including commuter benefits and a well-located office in Montreal
  • Hybrid work model (2–3 days in office per week)


Why Apply

If you like tidy datasets and predictable problems, this probably isn’t your role. This is messy, real-world data at scale, where things break, drift, and evolve constantly. But if you’re the kind of engineer who wants to build systems that actually shape how cities are understood, and you get a kick out of turning complexity into something usable, this is worth your time. Apply if you want your work to matter beyond dashboards and pipelines.