160 Data Training jobs in Canada

Huawei Canada has an immediate permanent opening for a Senior Researcher.

About the team:

The Computing Data Application Acceleration Lab aims to create a leading global data analytics platform organized into three specialized teams using innovative programming technologies. This team focuses on full-stack innovations, including software-hardware co-design and optimizing data efficiency at both the storage and runtime layers. This team also develops next-generation GPU architecture for gaming, cloud rendering, VR/AR, and Metaverse applications.

One of the goals of this lab are to enhance algorithm performance and training efficiency across industries, fostering long-term competitiveness.

About the job:

• Track the emerging technical trends and developments for big data and AI systems in both industry and academia, conduct in-depth insight and survey analysis, and identify the direction of key cutting-edge technologies for AI-powered big data systems.

• Collaborate closely with stakeholders to comprehend their business needs thoroughly. Translate these requirements into innovative and effective technology solutions that align with organizational objectives.

• Analyze and define key software requirements and features, develop the proof-of-concept (PoC) AI-powered big data system infrastructure (based on our existing infrastructure) and optimize its performance and performance per cost.

• Integrate the PoC system into our existing product and deliver it to the production team.

• Generate intellectual property such as patents and trade-secrets from research findings, and/or publish papers in peer-reviewed scientific journals/conferences.

• Present research findings at conferences and participate in research collaborations with external research institutes and universities.

Job Description

Qorsa Corp is a Canadian technology company pioneering quantum-proof AI solutions for governments, enterprises, and institutions. We build and integrate advanced machine learning with cryptographically agile systems built for the post-quantum era to help our clients better understand and protect their data.

As a Machine Learning engineer, you’ll work on data ingestion and processing using various Natural Language Processing (NLP) tools. You will also work on building AI agents, fine-tuning LLMs, and building chatbots.

Key responsibilities include:

• Design, build, and maintain AI Agents using Langchain and other similar tools.

• Fine-tune and test LLMs on various verticals explored by Qorsa.

• Develop and deploy applications using Docker and Kubernetes.

• Improve on our existing technologies including data processing, natural language pipelines, and building knowledge graphs

Qorsa Corp is a Canadian technology company pioneering quantum-proof AI solutions for governments, enterprises, and institutions. We build and integrate advanced machine learning with cryptographically agile systems built for the post-quantum era to help our clients better understand and protect their data.

Qorsa Corp is a Canadian technology company pioneering quantum-proof AI solutions for governments, enterprises, and institutions. We build and integrate advanced machine learning with cryptographically agile systems built for the post-quantum era to help our clients better understand and protect their data.

Job Description

Salary: $100,000-$25,000+ yearly salary + benefits (See below for more details)

About us:

Spring Financial is revolutionizing financial access for Canadians, providing smart credit-building, mortgage, and lending solutions. Millions struggle with high-interest debt and limited financial optionswere here to change that.
As one of Canadas fastest-growing fintech companies, annually we help 1 million customers explore their financing options with easeonline, via text, or over the phone. Our dynamic, innovative team thrives on collaboration, growth, and making a real impact.
To learn more about our products please visit our website here:

NOTE: This is a full-time, permanent, hybrid position in downtown Vancouver, with 3 set days in the office and 2 WFH.

Job Overview:

As a Machine Learning Engineer II, you independently design, build, and maintain machine learning systems that deliver impact for our customers and business. You are responsible for deploying reliable, scalable solutions from credit scoring models to intelligent automation and LLM-powered features. You work across the stack to connect ML systems with real user value.

You own end-to-end workflows: from data ingestion and transformation to model training, validation, and online inference. You actively contribute to model quality, observability, and performance optimization. You also help standardize development practices, CI/CD, and deployment tooling for ML systems.

You are expected to integrate modern AI techniques including LLM APIs, embeddings, and generative workflows where appropriate, and help evaluate how they can enhance products and operations. You use AI development tools to accelerate delivery and improve testing and debugging. You also build and maintain automated data pipelines and model services, working across real-time and batch systems.

You work closely with product managers, data scientists, and business stakeholders to clarify problems, evaluate feasibility, and align technical solutions with strategic outcomes. You are a key contributor to the evolution of Springs ML platform and culture.

What youll do:

• Own development of production-grade ML and AI systems from data to deployment.
• Build automated pipelines for training, feature engineering, and model serving.
• Use AI tools to improve development speed and integrate AI capabilities (e.g. LLMs) into products.
• Optimize systems for performance, latency, and cost.
• Collaborate with cross-functional stakeholders to scope projects and communicate results.
• Monitor, retrain, and improve models based on feedback and system metrics.
  
  

What You Should Already Have:

• Experience deploying machine learning models into production systems.
• Proficiency in Python and tools such as scikit-learn, TensorFlow, PyTorch, or HuggingFace.
• Strong understanding of model lifecycle, MLOps, and data pipeline design.
• Skills in inference optimization.
• Ability to collaborate with data, product, and business teams on impactful ML features.
• Experience with testing, monitoring, and CI/CD for ML systems.
• Know-hows on cost/benefit analysis for different ML solutions, e.g. Lambda vs. Sagemaker Inference, OpenAI vs. xAI API.
• Comfortable working with AI technologies (LLMs, embeddings, etc.) in applied settings.

What We Will Give You:

• Competitive annual salary ranging from 100,000 to 125,000+ , reflective of experience and impact.
• Comprehensive benefits package, including extended health, dental, and vision coverage with 100% of monthly premiums covered by the Spring.
• GRSP matching program to support your long-term financial goals.
• Transit-Friendly Employer (Transit allowance).
• A modern, collaborative workspace in the heart of downtown Vancouver.
• Ongoing career growth opportunities and the chance to help shape Spring Financials technology strategy and team culture.

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Please note : Upon applying, our Talent Acquisition team will review your resume. If you qualify, we will reach out to learn more about your experience and answer any questions you may have about the role, benefits, compensation, and more. Due to high application volume, we may not be able to respond to everyone.

Thank you for your interest! We appreciate your time and look forward to reviewing your application!

Job Description

Our client is looking for a highly skilled Machine Learning Engineer to join their growing team in Mississauga. This role is ideal for a technically strong and experienced ML professional who thrives in a fast-paced, collaborative environment and is passionate about delivering scalable machine learning solutions on distributed systems such as Hadoop.

Key Responsibilities:

• Design, develop, and implement machine learning models using Spark ML for predictive analytics
• Build and optimize end-to-end training and inference pipelines on distributed platforms
• Process and analyze large datasets to uncover insights and engineer effective features
• Work closely with data engineers to integrate ML models into existing data pipelines
• Fine-tune models and hyperparameters to maximize performance and accuracy
• Develop scalable solutions for both real-time and batch inference
• Continuously monitor deployed models and address any performance issues
• Keep up-to-date with the latest tools, frameworks, and best practices in machine learning and distributed computing

• 10+ years of experience as a Machine Learning Engineer or similar role
• Expertise in Apache Spark and Spark MLlib
• Solid understanding of predictive modeling techniques (e.g., regression, classification, clustering)
• Hands-on experience with distributed systems such as Hadoop
• Proficiency in Python, Scala, or Java
• Strong grasp of data preprocessing and feature engineering methodologies
• Familiarity with model evaluation metrics and production deployment practices
• In-depth knowledge of distributed computing and parallel processing principles