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Added 2 hours ago
IS
Junior Software Engineer
Iris Software Inc.
Toronto, ON · Greater Toronto Area, Canada
- Full-time
We are seeking a Junior Software Engineer with a strong Computer Science background and exposure to Generative AI (GenAI) technologies. The candidate will support the design, development,…
Added 4 hours ago
GT
Lead Data Engineer / Data Product Lead – Snowflake
Global Technical Talent, an Inc. 5000 Company
Toronto, ON
- $60 to $80 CAD / hour
- Contract
…Lead Data Engineer / Data Product Lead to support the design and delivery of enterprise-scale data products within a complex life sciences environment. This is a hands-on technical…
Added 4 hours ago
D
Full Stack Developer (Java/Python + Gen AI)
Digitalogia
Brampton, ON
- Contract
Role Description This is a contract Full Stack Developer (Java/Python + Gen AI) role based in Brampton, ON with a hybrid work arrangement, allowing a mix of on-site and work-from-home days.…
Added 6 hours ago
TT
Senior MLOps Engineer - Investment Banking
Tech Talent International
Montreal, QC
- $140,000 to $150,000 CAD / year
- Full-time
Senior-level Python development across the full data and ML stack.
Added 11 hours ago
F
Senior Machine Learning Engineer
Fusemachines
Remote, Canada
- Contract
- Remote
You must possess a strong hybrid skill set: deep expertise in applied machine learning combined with production-grade software engineering skills. You will not just build models in…
Added 18 hours ago
H
Senior WMS Implementation Engineer
Hays
Canada
- $95 to $100 CAD / hour
- Contract
Proficient in Python for data science and GenAI application development
Added 22 hours ago
IF
Senior Full stack AI Developer (Python & Angular/React)
Intact FC
Toronto, ON · Montreal, QC
- Full-time
Flexible work arrangements and a hybrid work model
Added 1 day ago
Senior Forward Deployed AI Engineer
Bell
Mississauga, ON
…choosing the right approach across automation, classical ML, and GenAI/agents, and taking solutions from rapid prototype to production-grade agentic workflows (such as multi-agent systems…
Added 1 day ago
SL
Senior Data Scientist
Sun Life
Toronto, ON · Waterloo, ON · Sun Life Toronto One York
- Full-time
Proficient in Python for data science and GenAI application development
Added 2 days ago
A
Forward Deployed Solutions Lead
Accenture
Calgary, AB · Ottawa, ON · Toronto, ON · Montreal, QC
- Full-time
Hybrid Azure and on-premises integration experience.
Added 2 days ago
API Lead Architect
Capgemini
Mississauga, ON
Exposure to GenAI/API integrations and cloud-native AI services.
Added 2 days ago
IS
ML Ops/AI Lead
Iris Software Inc.
Toronto, ON
- Full-time
Proficient in Python and its ecosystem of tooling such as Jupyter Notebooks, Packaging, Documentation
Added 2 days ago
I
Software Developer 1 - API Management Platform
Intuit
Toronto, ON
- Full-time
Provides Starter code, GenAI based tooling and SDKs for API Producers to produce world class APIs and API consumers to discover and consume these APIs with ease.
Added 2 days ago
ES
GEN AI Developer
Epsilon Solutions Ltd.
Mississauga, ON
- Contract
Experienced professional with strong Python development and Generative AI expertise, especially in prompt engineering.
Added 2 days ago
C
AI Architect-Governance & Delivery Lead
CGI
Toronto, ON
- Full-time
…Candidates must demonstrate production experience designing GenAI, RAG, and agentic solutions, and applying AI-assisted engineering to improve productivity, quality, and delivery…
Added 3 days ago
AI
Forward Deployed Engineer (Python/Pyspark and GenAI / LLM)
Apptoza Inc.
Toronto, ON
- Full-time
Role: Forward Deployed Engineer (Python/Pyspark and GenAI / LLM)
Added 3 days ago
S
GenAI Python Developer
Synechron
Montreal, QC · MDC – Montreal
- Full-time
Nous recherchons un Développeur Python GenAI hautement technique ayant une expérience démontrée dans la conception, le développement et le déploiement d’applications d’intelligence…
Added 3 days ago
IF
AI Developer Senior
Intact FC
Montreal, QC
- Full-time
Flexible work arrangements and a hybrid work model
Added 3 days ago
S
Enterprise Architect – AI, Data & Cloud
Synechron
Mississauga, ON
- $180,000 to $200,000 CAD / year
- Full-time
Develop strong technical points of view across cloud, data, AI/ML and GenAI, integration, APIs, security, and emerging technologies.
Added 3 days ago
Q-
MONTREAL [hybrid] - MLOps Engineer
QUANTEAM - North America (RAINBOW PARTNERS Group)
Montreal, QC · Greater Montreal Metropolitan Area
- Full-time
Senior-level Python development across the full data and ML stack.
Added 3 days ago
AS
AWS Cloud Architect
Ardent SoftSol Inc.
Mississauga, ON
- $50 to $55 CAD / hour
- Contract
Design hybrid and multi-cloud integrations where applicable.
Added 3 days ago
JG
AWS / API lead and Architect
J&M Group
Mississauga, ON
- Contract
Design hybrid and multi-cloud integrations where applicable.
Added 3 days ago
M
Associate Applied AI Engineer – GenAI Systems
Manulife
Toronto, ON
- Full-time
Manulife is making a significant investment in Advanced Analytics and GenAI to transform how Finance, Treasury, and Actuarial teams make decisions. Our AI team builds practical, governed…
Added 4 days ago
HO
Senior AI Engineer
Hydro One
Toronto, ON
- $90 to $110 CAD / hour
- Contract
Design scalable GenAI decision-support systems for business and executive users
Added 4 days ago
A
Prompt Engineer - IA générative
Astek
Montreal, QC
- Full-time
As a GenAI Prompt Engineer, you will join a machine learning squad. You will work with internal clients and subject-matter experts to understand their needs, translate them into effective…

Fusemachines

Senior Machine Learning Engineer

Remote, Canada

Remote

Contract

Apply About employer

Applications open in a new tab.

Job details

Job type: Contract
Workplace: Remote
Apply by: Dec 20, 2026
Experience: 5–8+ years of experience as a Machine Learning Engineer or Software Engineer focusing on ML systems, ideally within Ad Tech, MarTech, or high-scale recommendation systems.
Posting language: English
Posted: Sep 21, 2026

Original job description

About Fusemachines

Fusemachines is a leading AI strategy, talent, and education services provider. Founded by Sameer Maskey Ph.D., Adjunct Associate Professor at Columbia University, Fusemachines has a core mission of democratizing AI. With a presence in 4 countries (Nepal, the United States, Canada, and the Dominican Republic) and more than 450 full-time employees, Fusemachines brings global AI expertise to transform companies worldwide. Founded in 2013, Fusemachines is a global provider of enterprise AI products and services, on a mission to democratize AI. Leveraging proprietary AI Studio and AI Engines, the company helps drive the clients’ AI Enterprise Transformation, regardless of where they are in their Digital AI journeys. With offices in North America, Asia, and Latin America, Fusemachines provides a suite of enterprise AI offerings and specialty services that allow organizations of any size to implement and scale AI. Fusemachines serves companies in industries such as retail, manufacturing, and government.

Fusemachines continues to actively pursue the mission of democratizing AI for the masses by providing high-quality AI education in underserved communities and helping organizations achieve their full potential with AI.

Type: Remote, Full-time

Role Overview

We’re hiring a Senior Machine Learning Engineer to architect, build, and deploy high-performance machine learning systems that power technology stack. You will work across the entire ML lifecycle - from processing massive volumes of data to developing and deploying low-latency models.

You must possess a strong hybrid skill set: deep expertise in applied machine learning combined with production-grade software engineering skills. You will not just build models in notebooks; you will write scalable, production-ready code, design real-time inference APIs, and ensure your systems meet strict latency and high-throughput requirements.

Key Responsibilities

Scale Data Engineering & Feature Pipelines

Process and extract features from massive, highly sparse datasets (terabytes/petabytes of bidstream and user event data) using SQL, Python, and distributed computing frameworks (e.g., Spark, Ray).
Architect offline and online feature pipelines. Manage real-time feature computation and low-latency feature stores ensuring zero online/offline skew.
Perform rigorous missingness analysis, leakage checks, and handle high-cardinality categorical variables safely.

Core ML & Deep Learning Development

Train, tune, and scale supervised learning models, utilizing advanced gradient boosting (XGBoost, LightGBM, CatBoost) and Factorization Machines.
Design and implement Deep Learning architectures for structured/recommendation data using PyTorch or TensorFlow.
Apply rigorous tabular modeling practices: meticulous leakage prevention, class imbalance strategies, and robust cross-validation on time-split data.

Productionization, MLOps, & System Engineering

Write clean, object-oriented, and modular production code. Transition models from Python research environments to high-performance serving environments (packaging with ONNX, TensorRT, etc).
Design and maintain robust MLOps pipelines: automated model retraining, versioning, shadow deployments, and CI/CD for machine learning.
Monitor production models for data drift, concept drift, and performance degradation in real-time, implementing automated alerting and fallback mechanisms.

Evaluation & Experimentation

Design rigorous A/B and multivariate tests to measure the true business incrementality of ML models.
Choose appropriate offline metrics (PR-AUC, normalized Entropy/LogLoss, Calibration, Lift) and bridge them to online business KPIs.

Success in This Role Looks Like

You deliver models that perform well and move business metrics (revenue lift, cost reduction, risk reduction, improved forecast accuracy, operational efficiency).
Your work is reproducible and production-aware: clear data lineage, robust evaluation, and a credible path to deployment/monitoring.
Stakeholders trust your judgment in selecting methods and communicating uncertainty honestly.

Required Qualifications

5–8+ years of experience as a Machine Learning Engineer or Software Engineer focusing on ML systems, ideally within Ad Tech, MarTech, or high-scale recommendation systems.
Production Engineering Skills: Strong software engineering fundamentals (OOP, data structures, algorithm design). Expert-level Python and strong proficiency in a compiled or high-performance language (e.g., C++, Java, Scala, Go, or Rust).
ML Systems & Serving: Deep experience deploying machine learning models into highly concurrent, low-latency production environments (APIs, microservices, Triton Inference Server, custom containers).
Distributed Computing: Hands-on experience with big data processing (Apache Spark, Kafka, Flink) and complex SQL queries.
Core ML & Deep Learning: Proven track record of shipping both tree-based models and neural networks (PyTorch/TensorFlow) to production.
Statistics & Experimentation: Solid grasp of statistics, hypothesis testing, and rigorous A/B experiment design.

Nice-to-Have

Agentic / GenAI Development: Experience designing agentic workflows or utilizing LLMs to automate ad creative generation, campaign copilot tools, or internal ML development workflows (AI-assisted IDEs, code agents).

Fusemachines is an Equal Opportunities Employer, committed to diversity and inclusion. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other characteristic protected by applicable federal, state, or local laws.

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More about this job

Responsibilities

The Senior Machine Learning Engineer will architect, build, and deploy high-performance machine learning systems across the entire ML lifecycle. Responsibilities include scaling data engineering pipelines, developing deep learning models, and maintaining production-grade MLOps infrastructure.

Requirements

Candidates must have 5–8+ years of experience in machine learning systems with strong software engineering fundamentals in Python and a high-performance language. Proficiency in distributed computing, deep learning frameworks, and production-level model deployment is required.

Skills

Machine Learning
Python
SQL
PyTorch
TensorFlow
Apache Spark
Distributed Computing
MLOps
Data Engineering
Feature Pipelines
XGBoost
LightGBM
CatBoost
System Architecture
A/B Testing
Statistics

Remote locations

Toronto, Ontario, Canada

Remote locations (standardized)

Toronto, Ontario, Canada

Visa sponsorship

Not detected in the job text

Keywords

Machine Learning
Artificial Intelligence
Data Engineering
Python
SQL
Spark
Ray
PyTorch
TensorFlow
XGBoost
LightGBM
CatBoost
MLOps
CI/CD
ONNX
TensorRT
Kafka
Flink
Triton Inference Server
A/B Testing
Statistics
Feature Stores
Distributed Computing
Software Engineering
Ad Tech
MarTech
Recommendation Systems
Data Drift
Model Deployment
Object-Oriented Programming

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