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Added 3 months ago
SD
Senior AI Engineer
Symbiotic Digital
Unorganized North Algoma, Ontario · Downtown Toronto (Ryerson), Ontario
- Contract
We are seeking a Senior AI Engineer to design, develop, and
Added 2 months ago
ST
Senior Data Engineer
Sensor Tower
Remote, Canada
- Full-time
- Remote
As Sensor Tower continues to grow as a global company, we are looking for a Senior Data Engineer to build amazing products together. We have a wonderful team of more than a hundred…
Added 4 months ago
H
Senior Flight-Operations Satellite Systems Engineer | Hybrid/Remote Opportunity
HIKINEX
Remote, Canada
- Full-time
- Remote
We are seeking a Senior Flight-Operations Satellite Systems Engineer to lead the design, integration, and optimization of advanced satellite operations for LEO and MEO missions. In this…
Added 4 months ago
H
Senior Mission & Operations Satellite Systems Engineer – Hybrid/Remote Opportunity | Fastwater Staaffing
HIKINEX
Remote, Canada
- Full-time
- Remote
Senior Mission & Operations Satellite Systems Engineer – Hybrid/Remote Opportunity
Added 2 months ago
Q
DFT Engineer (Senior to Staff level)
Qualcomm
Toronto, ON
- Full-time
…create a smarter, connected future for all. As a Qualcomm DFT Engineer, you will plan, design, optimize, verify, and test electronic systems, bring-up yield, circuits, mechanical systems,…
Added 4 months ago
A
Staff Software Engineer, Shared Services ⭐
Achievers
Toronto, ON
- Full-time
…feature flag management, and the base libraries that every Go and Python service at Achievers is built on - all sitting at the critical path of everything we…
Added 1 month ago
Senior ML Data Processing Developer
LawZero
Montreal, QC
We are seeking a Senior ML Data Processing Developer to participate in the development, curation, and scaling of our core data asset pipeline. Sitting at the intersection of data…
Added 4 months ago
Senior CI/CD & DevOps Solution Engineer
Staffinity Inc
Halifax, Nova Scotia
Staffinity is currently seeking a Senior CI/CD & DevOps Solution Engineer for a premier corporate client located in Halifax. This is a full-time position offering a competitive salary and…
Added 4 months ago
KC
Forward Deployed AI Engineer
Keyrus Canada
Toronto, ON · Montreal, QC
- Full-time
We are currently building our talent pipeline for upcoming Forward Deployed AI Engineer opportunities in Canada. While we may not have an immediate opening today, we are actively connecting…
Added 4 months ago
HB
Senior DevOps Engineer
Haventree Bank
Toronto, ON
- Full-time
Reporting to the Lead DevOps Engineer at Haventree Bank, you will be responsible for designing, implementing and managing a secure and efficient DevOps process as well as cloud…
Added 2 months ago
Senior Software Enginner- Global Payments Engineering
Scotiabank
Toronto, ON · Scarborough, ON
Technical understanding – as a standard Software Engineer there will be expectations that you are able to lead technical discussions, challenge design and strategy
Added 3 months ago
M
Senior Site Reliability Engineer
Morningstar
Toronto, Ontario
- Full-time
Write scripts and tooling in Python, Bash, or other scripting languages to automate routine operational tasks and streamline deployments.
Added 2 months ago
Q
DFT Engineer, Principal
Qualcomm
Toronto, ON
- Full-time
…create a smarter, connected future for all. As a Qualcomm DFT Engineer, you will plan, design, optimize, verify, and test electronic systems, bring-up yield, circuits, mechanical systems,…
Added 2 months ago
Q
Senior Director, Technology
Qualcomm
Ottawa, ON
- Full-time
…create a smarter, connected future for all. As a Qualcomm ASIC Engineer, you will define, model, design (digital and/or analog), optimize, verify, validate, implement, and document IP…
Added 4 months ago
KC
Senior Satellite Systems Designer - Platform Architect
Kepler Communications
Toronto, ON
- Full-time
As a Senior Systems Engineer, you will be a technical leader contributing across multiple satellite and space-system programs. You will help deliver critical subsystems, system-level work…
Added 4 months ago
KC
Satellite Systems Designer - Analysis & Support
Kepler Communications
Toronto, ON
- Full-time
As a Systems Engineer, you will support satellite and payload development programs by contributing to mission analysis, system-level engineering, payload integration, verification planning,…
Added 4 months ago
CS
Inference ML API SDET
Cerebras Systems
Toronto, Ontario
- Full-time
As a Senior Software Engineer in Test for the ML API features team, you will lead testing strategy and execution for AI/ML models, evaluating accuracy, fairness, and performance at scale.…
Added 2 months ago
Q
Connectivity Systems Engineer, Staff
Qualcomm
Toronto, ON
- Full-time
As a connectivity systems engineer, you'll define and develop the technologies that underlie the next generation of our products. The ideal candidate will have extensive hands-on experience…
Added 4 months ago
P
Senior AI Engineer
Paytm
Toronto, Ontario
- Full-time
Proficiency in Python across a broad stack - pipeline, agent, service, and instrumentation.
Added 4 months ago
Q
Senior Full Stack Engineer
Quandri
Vancouver, British Columbia
- Full-time
As a Full Stack Engineer at Quandri, you will be directly responsible as an IC leader of a team that builds our revenue-generating customer-facing product offerings on our intelligence…
Added 4 months ago
Senior Machine Learning Engineer - Computer Vision
Citylogix
Montreal, Quebec
Reporting to the Chief Technology Officer (CTO), the Senior Machine Learning Engineer is responsible for researching, developing, and deploying the computer-vision models at the core of our…
Added 4 months ago
D
Senior Software Engineer, Backend
d1g1t
Toronto, Ontario
- Full-time
We are looking for a Senior Software Engineer, Backend to join our engineering team and contribute to a large, complex production platform used by sophisticated financial services clients.
Added 4 months ago
CC
Senior Hardware Engineer (Systems) - Onsite Position
Curtiss-Wright Corporation
Ottawa, Ontario · Canada-Ottawa
- Full-time
Senior Hardware Engineer (Systems)- Onsite Position
Added 4 months ago
BI
Senior Solutions Engineer
Burq, Inc.
Remote, Canada
- Full-time
- Remote
The Senior Solutions Engineer is Burq’s technical closer. You own the technical side of every deal - from first discovery call through signed contract - partnering closely with Account…
Added 4 months ago
IL
Senior Software Quality Engineer
Invesco Ltd.
Charlottetown, Prince Edward Island
- Full-time
The Senior Software Quality Engineer leads the design, execution, and oversight of complex test strategies to ensure the delivery of high quality, reliable software products for Invesco’s…

Citylogix

Senior Machine Learning Engineer - Computer Vision

Montreal, QC, Canada

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Job details

Experience: Minimum of 5 years of applied machine-learning / computer-vision experience, or a graduate degree (MSc/PhD) ina relevant field plus 3+ years of applied experience
Posting language: English · French
Posted: Jun 26, 2026

Original job description

English section of this bilingual listing.

About the role

Reporting to the Chief Technology Officer (CTO), the Senior Machine Learning Engineer is responsible for researching, developing, and deploying the computer-vision models at the core of our platform - the segmentation systems that detect infrastructure defects and map road assets from large-scale imagery.

This is a hands-on technical role focused on transformer-based segmentation. You will own models from research through production: improving accuracy and robustness, generalizing models across different camera systems, consolidating task-specific models into unified architectures, and partnering with our DevOps and Engineering teams to bring them reliably into production at scale.

What you'll do

Research, design, train, and evaluate deep-learning models for semantic, instance, and panoptic segmentation, applied to infrastructure-defect detection and road-asset/scene segmentation
Fine-tune and adapt transformer-based segmentation architectures (e.g., Mask2Former, OneFormer, and DETR-family models, including custom in-house variants) Improve domain generalization so models perform reliably across heterogeneous
camera systems and imaging conditions, both individually and in combination
Consolidate multiple task- or defect-specific checkpoints into unified, multi-task models to simplify the production footprint
Partner with the DevOps team to train, deploy, and monitor models on AWS (including Amazon SageMaker), and to optimize inference performance and cost
Build and maintain reproducible training pipelines, evaluation benchmarks, and dataset/annotation workflows
Diagnose model failures and data-quality issues, and drive measurable improvements in accuracy, robustness, and efficiency
Track emerging architectures and techniques, and recommend where they create real value for the platform
Maintain clear technical documentation, experiment records, and model-versioning standards

Qualifications

Minimum of 5 years of applied machine-learning / computer-vision experience, or a graduate degree (MSc/PhD) ina relevant field plus 3+ years of applied experience
Strong, hands-on proficiency with PyTorch
Demonstrated experience with deep-learning segmentation (semantic, instance, and/or panoptic) on real-world image data
Practical experience with transformer-based vision architectures (Mask2Former, OneFormer, DETR, or similar)
Solid command of fine-tuning, transfer learning, and domain-adaptation/generalization techniques
Experience with the Hugging Face ecosystem and/or detectron2
Comfort training and deploying models in a cloud environment (AWS preferred; experience with Amazon SageMaker a strong asset)
Strong Python engineering skills and good software practices (version control, testing, reproducibility)
Excellent communication and collaboration skills, and the ability to manage priorities in a fast-paced environment

Nice to Have

Experience working with imagery from industrial, line-scan, or panoramic camera systems
Background in geospatial / GIS, remote sensing, or infrastructure/civil applications
MLOps experience: model lifecycle management, monitoring, and CI/CD for ML
Model-optimization experience (quantization, distillation, ONNX/TensorRT, or similar) for efficient inference
Experience unifying multi-task or multi-model systems into consolidated architectures
Experience in a fast-growing SaaS or technology-driven organization

Read the full bilingual original

About the role

What you'll do

Research, design, train, and evaluate deep-learning models for semantic, instance, and panoptic segmentation, applied to infrastructure-defect detection and road-asset/scene segmentation
Fine-tune and adapt transformer-based segmentation architectures (e.g., Mask2Former, OneFormer, and DETR-family models, including custom in-house variants) Improve domain generalization so models perform reliably across heterogeneous
camera systems and imaging conditions, both individually and in combination
Consolidate multiple task- or defect-specific checkpoints into unified, multi-task models to simplify the production footprint
Partner with the DevOps team to train, deploy, and monitor models on AWS (including Amazon SageMaker), and to optimize inference performance and cost
Build and maintain reproducible training pipelines, evaluation benchmarks, and dataset/annotation workflows
Diagnose model failures and data-quality issues, and drive measurable improvements in accuracy, robustness, and efficiency
Track emerging architectures and techniques, and recommend where they create real value for the platform
Maintain clear technical documentation, experiment records, and model-versioning standards

Qualifications

Minimum of 5 years of applied machine-learning / computer-vision experience, or a graduate degree (MSc/PhD) ina relevant field plus 3+ years of applied experience
Strong, hands-on proficiency with PyTorch
Demonstrated experience with deep-learning segmentation (semantic, instance, and/or panoptic) on real-world image data
Practical experience with transformer-based vision architectures (Mask2Former, OneFormer, DETR, or similar)
Solid command of fine-tuning, transfer learning, and domain-adaptation/generalization techniques
Experience with the Hugging Face ecosystem and/or detectron2
Comfort training and deploying models in a cloud environment (AWS preferred; experience with Amazon SageMaker a strong asset)
Strong Python engineering skills and good software practices (version control, testing, reproducibility)
Excellent communication and collaboration skills, and the ability to manage priorities in a fast-paced environment

Nice to Have

Experience working with imagery from industrial, line-scan, or panoramic camera systems
Background in geospatial / GIS, remote sensing, or infrastructure/civil applications
MLOps experience: model lifecycle management, monitoring, and CI/CD for ML
Model-optimization experience (quantization, distillation, ONNX/TensorRT, or similar) for efficient inference
Experience unifying multi-task or multi-model systems into consolidated architectures
Peer-reviewed publications or open-source contributions in computer vision
Experience in a fast-growing SaaS or technology-driven organization

Version française:

À propos du rôle

Relevant du chef de la direction technologique (CTO), l'ingénieur principal ou l'ingénieure principale en apprentissage automatique est responsable de la recherche, du développement et du déploiement des modèles de vision par ordinateur au cœur de notre plateforme. Ceux-ci comprennent notamment les systèmes de segmentation qui détectent les défauts d'infrastructure et cartographient les actifs routiers à partir d'images acquises à grande échelle.

Il s'agit d'un rôle technique pratique, axé sur la segmentation par transformeurs. Vous prendrez en charge l'ensemble du cycle de vie des modèles, de la recherche à la mise en production : amélioration de la précision et de la robustesse, généralisation des modèles à différents systèmes de caméras, consolidation de modèles spécialisés en architectures unifiées, et collaboration avec les équipes DevOps et de développement afin d'assurer leur déploiement fiable et à grande échelle.

Responsabilités principales

Concevoir, entraîner et évaluer des modèles d'apprentissage profond pour la segmentation sémantique, par instance et panoptique, appliqués à la détection de défauts d'infrastructure ainsi qu'à la segmentation des actifs et des scènes routières.
Adapter et affiner (fine-tuning) des architectures de segmentation par transformeurs (p. ex. Mask2Former, OneFormer et les modèles de la famille DETR, y compris des variantes internes).
Améliorer la généralisation des modèles afin d'assurer une performance fiable sur différents systèmes de caméras et dans diverses conditions d'imagerie, individuellement ou en combinaison.
Consolider plusieurs points de contrôle (checkpoints) spécialisés en modèles multitâches unifiés afin de simplifier l'architecture de production.
Collaborer avec l'équipe DevOps pour entraîner, déployer et surveiller les modèles sur AWS (y compris Amazon SageMaker), tout en optimisant les performances et les coûts d'inférence.
Concevoir et maintenir des pipelines d'entraînement reproductibles, des bancs d'évaluation ainsi que des flux de travail liés aux jeux de données et à l'annotation.
Diagnostiquer les défaillances des modèles et les problèmes de qualité des données, puis mettre en œuvre des améliorations mesurables en matière de précision, de robustesse et d'efficacité.
Assurer une veille technologique sur les nouvelles architectures et techniques, puis recommander celles qui apportent une réelle valeur ajoutée à la plateforme.
Maintenir une documentation technique claire, des registres d'expériences et des normes de gestion des versions des modèles.

Exigences du poste

Minimum de cinq (5) années d'expérience appliquée en apprentissage automatique ou en vision par ordinateur, ou une maîtrise (M. Sc.) ou un doctorat (Ph. D.) dans un domaine pertinent accompagné d'au moins trois (3) années d'expérience appliquée.
Solide maîtrise pratique de PyTorch.
Expérience démontrée en segmentation par apprentissage profond (sémantique, par instance et/ou panoptique) appliquée à des images réelles.
Expérience pratique des architectures de vision par transformeurs (Mask2Former, OneFormer, DETR ou équivalent).
Bonne maîtrise des techniques de fine-tuning, d'apprentissage par transfert (transfer learning) et d'adaptation ou de généralisation de domaine.
Expérience avec l'écosystème Hugging Face et/ou Detectron2.
Aisance à entraîner et à déployer des modèles dans un environnement infonuagique (AWS de préférence; une expérience avec Amazon SageMaker constitue un atout important).
Solides compétences en développement logiciel Python ainsi qu'en bonnes pratiques de développement (gestion des versions, tests et reproductibilité).
Excellentes aptitudes en communication, en collaboration et en résolution de problèmes, ainsi que la capacité à gérer plusieurs priorités dans un environnement dynamique.

Atouts

Expérience avec l'imagerie provenant de caméras industrielles, linéaires (line-scan) ou panoramiques.
Expérience en géomatique (SIG), en télédétection ou dans des applications liées aux infrastructures et au génie civil.
Expérience en MLOps, notamment en gestion du cycle de vie des modèles, en surveillance et en CI/CD appliqués à l'apprentissage automatique.
Expérience en optimisation de modèles (quantification, distillation, ONNX, TensorRT ou équivalent) afin d'améliorer l'efficacité de l'inférence.
Expérience dans l'unification de systèmes multitâches ou multimodèles au sein d'architectures consolidées.
Publications évaluées par les pairs ou contributions à des projets de vision par ordinateur à code source ouvert.
Expérience au sein d'une entreprise technologique ou d'une entreprise SaaS en forte croissance.

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More about this job

Responsibilities

Research, develop, and deploy transformer-based computer vision models for infrastructure defect detection and road asset mapping. Collaborate with DevOps to optimize model inference and maintain reproducible training pipelines on AWS.

Requirements

Requires at least 5 years of applied ML/CV experience or a postgraduate degree with 3+ years of experience. Must be proficient in PyTorch, Python, and deep-learning segmentation architectures.

Skills

PyTorch
Computer Vision
Deep Learning
Semantic Segmentation
Instance Segmentation
Panoptic Segmentation
Transformer Architectures
Python
AWS
Amazon SageMaker
Hugging Face
Detectron2
Domain Adaptation
Transfer Learning
MLOps
Software Engineering

Visa sponsorship

Not detected in the job text

Keywords

Machine Learning
Computer Vision
PyTorch
Python
AWS
Amazon SageMaker
Mask2Former
OneFormer
DETR
Semantic Segmentation
Instance Segmentation
Panoptic Segmentation
Hugging Face
Detectron2
MLOps
ONNX
TensorRT
Quantization
Distillation
GIS
Remote Sensing
SaaS
CI/CD
Domain Generalization
Multi-task Learning

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