Machine learning • toronto on
About PureFacts Financial Solutions.PureFacts is a revenue performance software company serving wealth management, asset management, and asset servicing firms.We help financial institutions protect...Show more
Reporting to the Production Supervisor, Machine Operator 1 is responsible for the safe and efficient operation of production line equipment, ensuring all products meet established quality and food ...Show more
Machine Learning — Master-Level Internship.Hours (approximately 3 months) .Remote (with hybrid options in Toronto).The Vosyn internship is unique.Remuneration is equivalent to $32.CAD per hour paya...Show more
We are looking for a highly skilled and pragmatic Machine Learning Engineer to work with us on the applied research, development, deployment, and optimization of advanced ML systems, Search, Inform...Show more
Despite massive investments in planning, forecasting, and analytics, retailers still face the same operational issues—out-of-stocks, bad master data, margin leakage, and inconsistent execution acro...Show more
Fox CorporationUnder the FOX banner, we produce and distribute content through some of the world’s leading and most valued brands, including: FOX News Media, FOX Sports, FOX Entertainment, FOX Tele...Show more
At Ouster, we build sensors and tools for engineers, roboticists, and researchers, so they can make the world safer and more efficient.We've transformed LIDAR from an analog device with thousands o...Show more
We are currently seeking talented individuals for a variety of positions, ranging from junior to senior levels, and will evaluate your application in its entirety.Layer 6 is the AI center of excell...Show more
Tiger Analytics is an advanced analytics consulting firm.We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data.Our consultants b...Show more
As a Machine Learning Engineer, you will help develop tailored user experiences using advanced LLMs, Knowledge Graphs, personalization, and predictive analysis.You will collaborate with other engin...Show more
Immediate Start - Machine Learning Researcher (PhD) – Systematic Commodities Hedge Fund.Moreton Capital Partners is rapidly expanding and seeking a talented Machine Learning Researcher to help desi...Show more
Toronto General Hospital Research.We're seeking a Postdoctoral Researcher in Machine Learning / Computer Science to help build the next frontier of deep learning, multimodal fusion, and longitudina...Show more
Primary Skill /s - Machine Learning to Customer Marketing initiatives -Python and libraries like PySpark, TensorFlow, PyTorch, and Scikit-learn big data ecosystems (e.Hadoop/Spark) and cloud platfo...Show more
About Fusemachines 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 com...Show more
At eBay, we're more than a global ecommerce leader — we’re changing the way the world shops and sells.Our platform empowers millions of buyers and sellers in more than 190 markets around the world....Show more
At RBC Borealis, you’ll be joining a team of leading researchers and software engineering specializing in machine learning.You will have access to rich and massive datasets, and to computational re...Show more
At RBC Borealis, you’ll be joining a team of leading researchers and software engineering specializing in machine learning.You will have access to rich and massive datasets, and to computational re...Show more
At Red Hat we believe the future of AI is open and we are on a mission to bring the power of open-source LLMs and vLLM to every enterprise.Inference team accelerates AI for the enterprise and bring...Show more
About PureFacts Financial Solutions
PureFacts is a revenue performance software company serving wealth management, asset management, and asset servicing firms. We help financial institutions protect, optimize, and grow revenue through a connected platform spanning pricing, billing, compensation, reporting, and transparency. By unifying fragmented data and workflows into a trusted revenue foundation, we help clients improve accuracy, strengthen governance, reduce manual effort, and unlock new growth opportunities.
At PureFacts, we are building an AI-native platform and company. We embed AI, intelligent automation, and agentic workflows across our products and operations to detect anomalies, surface insights, streamline repetitive work, and support faster, better decision-making. In a highly regulated industry, we believe AI must be practical, governed, and auditable—amplifying human expertise while helping our teams and clients focus on higher-value, strategic work.
About the role
The Machine Learning Platform Engineer will be responsible for building and scaling the infrastructure that powers AI and machine learning across PureFacts’ platform. This role sits at the intersection of data engineering, platform engineering, and machine learning, ensuring that ML models can be reliably developed, deployed, monitored, and scaled in production environments.
You will play a critical role in enabling PureFacts’ AI-first strategy by creating systems and pipelines that allow teams to deliver AI solutions efficiently, automate workflows, and reduce operational overhead.
What you'll do
AI Infrastructure & Platform Development
Design and build scalable ML infrastructure and platforms to support model development and deploymentDevelop systems that enable rapid experimentation, testing, and deployment of AI modelsCreate reusable frameworks and tooling to standardize ML workflows across teamsMLOps & Model Lifecycle Management
Establish and maintain end-to-end MLOps pipelines, including:Data ingestion and preprocessingModel training and validationDeployment and versioningMonitoring and performance trackingImplement best practices for CI/CD for machine learning systemsEnsure reproducibility, reliability, and traceability of modelsAutomation & Efficiency
Build systems that automate repetitive ML and data workflows, reducing manual effortEnable teams to deploy and manage models with minimal operational overheadSupport the broader goal of eliminating low-value work through automation and intelligent systemsData Pipeline & Integration
Develop and maintain robust data pipelines and feature storesEnsure high-quality, scalable data flows for training and inferenceIntegrate ML systems into PureFacts’ SaaS platform and client-facing applicationsCloud & Scalable Systems
Design and manage infrastructure on cloud platforms (Azure-based)Optimize for scalability, performance, and cost efficiencyWork with containerization and orchestration tools (Docker, Kubernetes)Monitoring, Observability & Reliability
Implement monitoring systems for:Model performance and driftData quality and pipeline healthSystem reliability and uptimeBuild alerting and logging systems to ensure proactive issue detection and resolutionCross-Functional Collaboration
Partner with data scientists, ML engineers, and product teams to operationalize modelsWork closely with engineering teams to integrate ML systems into production environmentsSupport teams in adopting AI and automation capabilities effectivelyGovernance & Security
Ensure infrastructure meets security, privacy, and compliance requirementsSupport responsible AI practices through:Model versioning and auditabilityData governance and access controls
Qualifications
Experience
3-5 yrs ML platform engineering for infrastructure, containerization, model serving, monitoring, drift detection, automated retraining pipelinesExperience building and maintaining production-grade ML systemsExperience in SaaS, fintech, or data-driven environments is preferredTechnical Skills
Strong programming skills in Python (required)Experience with:Data processing (SQL, Spark)ML frameworks (TensorFlow, PyTorch, Scikit-learn)MLOps tools (MLflow, Kubeflow, Airflow, etc.)Experience with:Cloud platforms (AWS, Azure, GCP)Containerization (Docker) and orchestration (Kubernetes)CI/CD pipelines and DevOps practicesInfrastructure & Systems Thinking
Strong understanding of distributed systems and scalable architectureExperience building feature stores, model registries, and data pipelinesAbility to design systems for performance, reliability, and maintainabilityAI & Automation Mindset
Passion for building systems that enable AI at scale and drive automationFocus on improving efficiency and reducing manual operational workInterest in emerging AI technologies and infrastructure trendsCommunication & Collaboration
Strong ability to work across technical and non-technical teamsAbility to explain infrastructure and system design decisions clearlyCollaborative mindset with a focus on team enablement and impact
Education
Degree in Computer Science, Engineering, Data Science, or related fieldAdvanced degree is a plus but not required
Key Success Metrics
Deployment speed and reliability of ML models in productionReduction in manual effort through automation of ML workflowsSystem scalability, uptime, and performanceAdoption of ML infrastructure and tools across teamsEfficiency gains in model development and deployment cyclesThe pay range for this role is:100,000 - 120,000 CAD per year(Toronto, Canada)
PI23a9c013f3c1-30511-40338408
){kind=logo}
){kind=logo}