111 AI Voice jobs in Canada

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

Who We Are:

Muniworth is an innovative SaaS startup dedicated to municipal financial forecasting, empowering local governments to optimize budgeting and strategic financial planning. We are currently building an advanced Machine Learning and AI team to develop internal tooling, enhance our web applications, and create customized solutions for our municipal clients. If you're passionate about leveraging machine learning to drive impactful real-world solutions, Muniworth is the ideal place for you.

Who You Are:

You're an experienced Machine Learning Engineer excited by the prospect of working closely with a talented ML and AI team, under the guidance of our brilliant Lead ML Engineer. You thrive in environments with varied, challenging projects ranging from classic supervised and unsupervised ML tasks to advanced NLP, LLM, and RAG implementations. You're highly proficient with ML frameworks and libraries and ML Ops tools, and love finding innovative ways to apply ML and AI in solving complex problems.

What You'll Do:

• Design, build, and deploy robust machine learning pipelines and model serving infrastructure, ensuring reliable ML workflows from training to production.
• Write clean, maintainable code following software engineering best practices - while this isn't a senior engineering role, candidates should have demonstrated competency in creating readable, well-structured solutions that support collaborative development.
• Collaborate closely with our Lead ML Engineer and ML/AI team on projects spanning classical ML techniques, including feature engineering, dimensionality reduction, clustering, and classification, as well as NLP, Large Language Models, and RAG.
• Optimize model performance and scalability, leveraging your expertise in ML frameworks, model optimization, and distributed computing systems.
• Develop internal ML tools and customized AI-driven solutions for municipal clients, significantly influencing our product direction and company strategy through advanced analytics and predictive modelling.
• Own and manage specific ML-focused projects, balancing responsibilities between model maintenance, performance monitoring, and research into new ML approaches and techniques.

Requirements

What You Bring:

• 3+ years of industry experience in machine learning engineering.
• Proficiency using PyTorch/TensorFlow for implementing custom neural networks and training processes.
• Demonstrated experience writing clean, maintainable code with attention to software engineering best practices.
• Experience using transformer libraries (e.g. Hugging Face) for text classification.
• Experience utilizing traditional ML algorithms creatively to solve complex classification tasks.
• Experience using MLflow or similar for experiment tracking and model registry
• Familiarity using Docker for containerization and orchestration
• Familiarity using Apache airflow for pipeline automation
• Familiarity using Fast API/Flask for model serving APIs
• Familiarity with GitHub Actions for CI/CD
• Exposure to using Redis and Elasticsearch for caching and search
• A master’s degree in computer science, mathematics, statistics, or a related field—or significant practical experience demonstrating equivalent expertise beyond an undergraduate level.
• Excellent problem-solving abilities and strong communication skills, with the capability to articulate complex technical concepts clearly.
• Enthusiasm for innovation, adaptability, and actively contributing to team objectives beyond traditional role boundaries

Benefits

Why Join Muniworth:

• Competitive salary and comprehensive health and dental benefits.
• Flexible working hours (40 hours/week), tailored to your preferred schedule.
• Collaborative, intellectually stimulating environment emphasizing mathematics, innovation, and technical excellence.
• Modern, welcoming office located centrally in downtown Victoria, BC—100% in-person role.
• Regular team-building events and optional social activities.
• Directly influence critical municipal financial infrastructure, making a tangible impact on communities and local governments.
• For an ideal candidate with exceptional experience, we are open to offering compensation beyond the listed salary range.

Hiring Process:

We're actively hiring and eager to onboard exceptional talent as soon as possible. If you're excited by the intersection of data engineering and machine learning, thrive in a dynamic startup environment, and are motivated by meaningful work that impacts municipal governance, we'd love to connect with you. Please include a link to your public GitHub repository!

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.

---

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!

Huawei Canada has an immediate 12-month contract opening for a Researcher.

About the team:

The Software-Hardware System Optimization Lab continuously improves the power efficiency and performance of smartphone products through software-hardware systems optimization and architecture innovation. We keep tracking the trends of cutting-edge technologies, building the competitive strength of mobile AI, graphics, multimedia, and software architecture for mobile phone products.

About the job:

• Work on machine learning research, in particular for continual learning and their application in large language models (LLMs).

• Evaluate algorithms on general ML benchmarks or large foundation models such as LLMs.

• Keeping up-to-date on recent advances in related fields.

Huawei Canada has an immediate 12-month contract opening for a Researcher.

About the team:

Founded in 2012, the Noah’s Ark lab has evolved into a prominent research organization with notable achievements in academia and industry. The lab’s mission focuses on advancing artificial intelligence and related fields to benefit the company and society. Driven by impactful, long-term projects, the aim is to enhance state-of-the-art research while integrating innovations into the company's products and services, including LLMs, RL, NLP, computer vision, AI theory, and Autonomous driving.

About the job:

• Participate in the innovative LLMs reasoning and LLMs empowered AI agent research project;

• Implement algorithms for proposed models and applications, deploy into internal product;

• Work closely with researchers in the team;

• Keeping up-to-date on selected areas of ML and writing scientific reports;

• Provide insight report on the latest literature work.

Job Description

Company Description

You will join a world-class team of engineers and data scientists from Facebook, Uber, Amazon and Google. We are a fast growing consulting firm based in Toronto with clients ranging from leading startups building impactful technologies to Fortune 500 companies looking to scale their engineering and data capabilities. 

We are looking for Data Scientists who are passionate about solving real world problems. You enjoy working with both structured and/or unstructured data and are motivated to productize scalable machine learning models. Critical thinking and problem-solving skills are essential for this role.

• BS (or higher, e.g., MS, or PhD) in Computer Science or related engineering field involving coding
• Experienced implementing and scaling machine learning models in production environments 
• Strong understanding of machine learning theory
• Hands on experience with Statistics
• Capable of quickly implementing prototypes of cutting-edge research papers
• Proficient in Python (i.e. Pandas, Numpy, scikit-learn, etc), R, TensorFlow, amongst other data science related tools and libraries
• Analytical mind and strong business acumen

If you're passionate about data science and is hungry to learn, please apply!

• We have competitive compensation.
• Work on cool projects based on your interests and skills. We believe in accountability and NOT micro-management.

Job Description

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 bring deep expertise in Data Science, Machine Learning, and AI. Our business value and leadership have been recognized by various market research firms, including Forrester and Gartner.

We are looking for a motivated and passionate Machine Learning Engineers for our team.

As part of this job, you will be responsible for:

• Providing solutions for the deployment, execution, validation, monitoring, and improvement of data science solutions
• Creating Scalable Machine Learning systems that are highly performant
• Building reusable production data pipelines for implemented machine learning models
• Writing production-quality code and libraries that can be packaged as containers, installed and deployed

Requirements

• Bachelor's degree or higher in computer science or related, with 5+ years of work experience
• Ability to collaborate with Data Engineers and Data Scientist to build data and model pipelines and help running machine learning tests and experiments
• Ability to manage the infrastructure and data pipelines needed to bring ML solution to production
• End-to-end understanding of applications being created and maintain scalable machine learning solutions in production
• Ability to abstract complexity of production for machine learning using containers
• Ability to troubleshoot production machine learning model issues, including recommendations for retrain, revalidate, and improvements
• Experience with Big Data Projects using multiple types of structured and unstructured data
• Ability to work with a global team, playing a key role in communicating problem context to the remote teams
• Excellent communication and teamwork skills

Additional Skills Required:

• Python, Spark, Hadoop, Docker, with an emphasis on good coding practices in a continuous integration context, model evaluation, and experimental design
• Test-driven development (prefer py. test/nose), experience with Cloud environments
• Proficiency in statistical tools, relational databases, and expertise in programming language like python/SQL is desired.

Good to have:

• Knowledge of ML frameworks like Scikitlearn, Tensorflow, Keras, etc.
• Knowledge of MLflow, Airflow, Kubernetes
• Knowledge on any of the cloud-native MLaaS offerings like AWS SageMaker, AzureML, or Google AI platform

Benefits

Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.