76 Computational Linguistics jobs in Canada

Job Description

Salary:

Come join Home Trust Company as a Machine Learning Engineerin our Data & Analytics team!

Home Trust Company has developed a track record of success as Canadas leading alternative lender, employing nearly 800 people in our Toronto headquarters and branches across the country. Building on the demonstrated strength of its core residential mortgage lending business, the Company also offers complementary lending services, as well as highly competitive deposit investment products, through Oaken Financial. Our culture has been shaped by the passion and integrity of our people. Home Trust is a private company.

FIRST THING WHAT YOU NEED TO SUCCEED?

We are looking for individuals who are dedicated, passionate, and driven to execute with excellence!

WE CARE ABOUT OUR EMPLOYEES WELL-BEING, WHAT WE OFFER:

• Base salary, with yearly incentive performance bonus

• Three (3) weeks of vacation, an additional six (6) flex days (sick or personal) in addition to statutory holidays

• Comprehensive benefit packages, offered through Manulife

• Group Retirement Savings Plan (GRSP) up to 8% contribution program & employer match

• $1000 Employee Referral Program

• Employee Discounts; phone plans, gym membership, Toronto Bike Share and many retailer discounts offered through WorkPerks

• Education Assistance program

ABOUT THE ROLE:

The Machine Learning Engineer role brings strong communication, analytic and technical skills. This role bridges the gap between data engineering and data science, requiring a deep knowledge of data processing, cloud platforms and machine learning technologies. The role encompasses both the development of machine learning models and the creation and maintenance of scalable data pipelines. Strong expertise in platforms such as Databricks, Azure, Python frameworks (Pandas, Numpy, etc.), Spark, is essential. Collaboration with data scientists, data engineers, data architects and software developers as well as business stakeholders is key to this role.

In addition:

• Design, develop and deploy machine learning models that address business challenges and add value to HTC objectives.
• Develop and maintain scalable data pipelines, ensuring data quality, reliability, and timeliness. Transform data into usable datasets for ML model development.
• Utilize platforms such as Databricks, Python, Azure for ML model development.
• Analyze large complex datasets to extract actionable insights and create innovative machine learning solutions.
• Refine and optimize existing ML and AI models and algorithms for performance and scalability.
• Monitor models for performance, accuracy and relevance.
• Collaborate with data scientists, software engineers, and other stakeholders to integrate machine learning solutions into production systems.
• Attend departmental meetings, learning events, participate in technical/professional activities as required.
• Create technical documentation for reference and reporting.
• Make sure models are free from biases and respect privacy and ethical guidelines.
• Perform research and development in latest trends in AI/ML, data science and data engineering to ensure companys and departments technological competitiveness.

WHAT WE REQUIRE:

• Authorized to work in Canada

• Great communication skills

• Bachelors or Masters degree in a STEM field (Computer Science, Engineering, Statistics, Mathematics, or a related field)

• 2+ years of experience in similar field
• Proven experience as a Machine Learning Engineer or a similar role (Data Engineering and/or data science). Proficiency in programming languages such as SQL, Python, Spark, R, SAS, etc.
• Solid understanding of machine learning frameworks (TensorFlow, PyTorch, or Keras).
• Experience with cloud platforms such as GCP, AWS, Azure. Experience with Big Data technologies such as Snowflake, Databricks, Hadoop, Spark, or similar.
  

PREREQUISITE: Maintain a positive supportive attitude, help to maintain an inclusive and supportive company culture!

Follow us on LinkedIn: Home Trust Company: My Company | LinkedIn

Job Description

Salary:

"I'm incredibly excited to welcome a new Machine Learning Engineer to our team! This role is perfect for someone passionate about diving deep into system architecture and large-scale, GPU-enabled high-performance computing clusters, optimizing AI workflows, and shaping the future of our infrastructure. We're looking for a collaborative individual who thrives on both technical excellence and guiding others, ultimately making a significant impact on our research productivity and the advancement of state-of-the-art AI models. I can't wait to see the innovative solutions you'll bring to Amii!"

Greg Burlet, Director of Engineering

About Amii

Alberta Machine Intelligence Institute (Amii) is one of Canadas three main institutes for artificial intelligence (AI) and machine learning, our world-renowned researchers drive fundamental and applied research at the University of Alberta (and other academic institutions), training some of the worlds top scientific talent. Our cross-functional teams work collaboratively with Alberta-based businesses and organizations to build AI capacity and translate scientific advancement into industry adoption and economic impact.

About the Role

The Machine Learning (ML) Engineer plays a key role in ensuring machine learning research and applied AI projects operate securely and effectively. As a key member of the team, the ML Engineer will collaborate with senior engineering leaders to deploy and manage computing infrastructure, optimize AI workflows, develop training materials, and contribute to the technical development of both individuals and the organization.

The ML Engineer will work with cross-functional teams and external partners to support the execution of research and applied projects. Specifically, this engineer will focus on implementing and managing the software stack of High-Performance Computing (HPC) systems and pipelines, ensuring efficient and effective allocation and utilization of compute resources such as GPUs, and providing support for users of these systems. This role is critical to advancing research productivity and enabling state-of-the-art machine learning models.

In addition to hands-on technical work, the ML Engineer will contribute to the strategic planning of our infrastructure, working alongside the Director, Engineering, and the Director, IT to develop strategies, playbooks, and best practices for optimizing our tools, frameworks, and services.

The role focuses on achieving excellence in three main accountabilities:

• Infrastructure and Systems Management
• AI Workflow Optimization
• Technical Coaching and Collaboration

Required Skills / Expertise

Key Responsibilities:

• Assists in the design, implementation, and management of High-Performance Computing (HPC) clusters to support AI research in machine learning (ML) and reinforcement learning (RL)
• Identifies and resolves end-user queries related to AI workflows, providing configuration support for software coding issues and infrastructure setups
• Oversees computing resources in the cloud or on premises to ensure secure and efficient operations, with a focus on optimizing resource utilization and availability for AI workflows
• Provides support by diagnosing and resolving technical issues, performing routine system maintenance, and enhancing the performance of supporting infrastructures
• Assists in the development and refinement of playbooks and strategies to maximize the use of tools, infrastructure, libraries, and frameworks
• Collaborates with university system administrators, AI researchers, and support staff to facilitate the integration and operation of AI/ML systems
• Leverages strong knowledge of Linux-based systems (e.g. Red Hat, CentOS, Ubuntu), proficiency in scripting languages (e.g. Bash, Python), Infrastructure as Code (e.g. terraform, ansible), container and orchestration systems (e.g., Docker, Kubernetes), and github workflows to automate tasks and optimize infrastructure performance
• Establishes monitoring and logging systems to track infrastructure performance, proactively detect anomalies, and ensure real-time alerts for system integrity and uptime
• Implements and maintains automated AI pipelines to streamline model development and ensure effective use of computational resources
• Monitors, assesses and analyzes data from ML projects to ensure effective model performance and project outcomes
• Utilizes strong analytical skills to visualize data, analyze statistical trends, and assess the effectiveness of AI software outputs
• Applies hands-on experience with AI tools and frameworks (e.g. TensorFlow, PyTorch, Keras) to support deep learning initiatives
• Installs, configures, and diagnoses software applications for machine learning algorithms and GPU-based computing to ensure seamless operation
• Participates in training, code reviews, and coaching to enhance team members' technical capabilities
• Designs and delivers technical training on AI/ML workflows, guiding researchers on how to optimize their workflows and make the most of available infrastructure resources
• Partners with the Director, Engineering and external partners (e.g. academic institutions and industry partners) to support ML projects

Qualifications:

• Post Secondary Degree in Computer Science, Information Technology, Data Science, or a related field
• Advanced Degrees or Certifications in High-Performance Computing (HPC), Computer Science, ML/AI or Cloud Infrastructure (nice to have)
• 3+ years of experience in systems architecture: DevOps / MLOps and multi-node compute clusters including networking, IaC (terraform, ansible), CI/CD pipelines, VMs and hypervisors (proxmox), linux, node provisioning (warewulf), containers and container orchestration (docker, kubernetes), logging stacks (ELK), and job schedulers (slurm)
• 5+ years of experience in Python programming with application to ML/RL (PyTorch, TensorFlow, distributed training with DDP or FSDP), systems administration, or software development roles in UNIX/Linux or large-scale HPC environments (experience working with GPUs preferred), as well as associated cloud computing platforms
• Knowledge and experience training reinforcement learning models nice to have
• Source Code Analysis: Proficiency in analyzing the source code of AI-based software
• Experience in academic or industry research environments
• Experience with optimizing large-scale AI models for resource efficiency

Attributes and Expectations:

• Advanced critical thinking and problem-solving skills
• Strong interpersonal communication skills for effective collaboration with internal teams and external stakeholders. Operates with integrity and trust
• Passion for designing effective learning exercises, technical concept illustrations, training, and evaluation tools
• Ability to manage multiple competing priorities in a fast-paced environment
• Demonstrates professional maturity, resourcefulness, and self-discipline in pursuing organizational goals
• A curious mindset with a keen interest in testing new educational tools and technologies
• Shows presence, self-confidence, sound judgment, and superior problem-solving abilities
• Fosters high-level cross-functional collaboration and establishes credibility while influencing peers to achieve common goals

What you'll love about us

• A professional yet casual work environment that encourages the growth and development of your skills.
• Participate in professional development activities
• Gain access to the Amii community and events
• A chance to learn from amazing teammates who support one another to succeed.
• Competitive compensation, including paid time off and flexible health benefits.
• A modern office located in downtown Edmonton, Alberta.

How to Apply

Were excited to add a new member to the Amii team for this role! We are keeping the door open to new applicants until we find the right fit. When sending your application, please send your resume and cover letter indicating why you think you'd be a fit for Amii. In your cover letter, please include one professional accomplishment you are most proud of and why.

Applicants must be legally eligible to work in Canada at the time of application.

Amii is an equal opportunity employer and values a diverse workforce. We encourage applications from all qualified individuals without regard to ethnicity, religion, gender identity, sexual orientation, age or disability. Accommodations for disability-related needs throughout the recruitment and selection process are available upon request. Any information provided by you for accommodations will be kept confidential and wont be used in the selection process.

Job Description

Salary:

"Im thrilled to welcome a new Machine Learning Engineer to our team! This role is perfect for someone passionate about driving trust and safety research. Were looking for someone with an applied mindset to join our diverse, cross-functional team, helping turn research into practical outputs that make an impact. I cant wait to see the contributions youll bring to Amii!"

Alyssa Lefaivre kopac, Director of AI Trust and Safety

About Amii

Alberta Machine Intelligence Institute (Amii) is one of Canadas three main institutes for artificial intelligence (AI) and machine learning, our world-renowned researchers drive fundamental and applied research at the University of Alberta (and other academic institutions), training some of the worlds top scientific talent. Our cross-functional teams work collaboratively with Alberta-based businesses and organizations to build AI capacity and translate scientific advancement into industry adoption and economic impact.

About the Role

Reporting to the Director of AI Trust and Safety, the ML Engineer will drive the development and execution of research and applied projects within the Trust and Safety portfolio. This role is pivotal in advancing state-of-the-art trust and safety research and delivering high-impact applied outputs.

As part of a rapidly growing team, the ML Engineer will play a central role in shaping the portfolio. The work will begin with a strong emphasis on research and will evolve toward developing applied tools and outputs as research findings are translated into practical, applied solutions. The ML Engineer will collaborate closely with senior engineering and research leaders to perform research, develop applied outputs, manage infrastructure, create training materials, and support the technical growth of both individuals and the organization.

In addition to hands-on technical work, the ML Engineer will work alongside the Director, Engineering and Director, AI Trust and Safety to develop strategies and best practices for optimizing our tools, frameworks, and services.

The role focuses on achieving excellence in three main accountabilities:

• Infrastructure and Systems Management
• Applied Research and Development
• Technical Coaching and Collaboration

Required Skills / Expertise

Key Responsibilities:

• Work with the Director, AI Trust and Safety and Applied Research Scientists to scope and define safety-focused project goals that balance foundational research with applied value.
• Perform research activities by implementing experiments, adapting models, and maintaining reproducible, well-documented code.
• Design and deliver training on AI/ML workflows for safety research, helping researchers optimize processes and infrastructure usage. Design and maintain data pipelines and compute environments to support safety-focused research, experimentation, and validation.
• Collaborate with internal teams and external partners to deliver practical tools, frameworks, and other applied outputs with real-world impact.
• Lead the engineering of safety tools and inference systems, ensuring outputs from safety research are secure, reliable, interoperable, and considered for real-world Trust & Safety applications.
• Develop and maintain model evaluation frameworks tailored to Trust & Safety research questions and use cases.
• Document systems, workflows, and best practices to ensure reproducibility, transparency, and effective knowledge sharing.
• Prepare and manage datasets including curation, preprocessing, and synthetic data generation to accelerate safety research.
• Collaborate with cross-functional teams to productize safety research outputs, build supporting tooling, and enable adoption by end users.
• Provide technical coaching, mentorship, and code reviews to staff, students, and partners on safety-focused ML development.

Qualifications:

• Post-graduate degree in Computer Science, Information Technology, Data Science, or a related field
• 3+ years of experience in ML engineering, with a strong track record in researching, designing, implementing, optimizing, and evaluating machine learning (ML) and reinforcement learning (RL) algorithms in both simulated and real-world environments.
• Demonstrated professional proficiency in developing and applying deep learning and RL algorithms using Python and modern machine learning frameworks (e.g., PyTorch, JAX, TensorFlow), with expertise in RL libraries and simulation environments (e.g., Gymnasium, MuJoCo, Stable-Baselines3, Dopamine, PureJaxRL), complemented by strong competency in Git-based version control and Unix/Linux environments.
• Experience working in academic or industry research environments, collaborating closely with research scientists.
• Advanced Degrees or Certifications in High-Performance Computing (HPC), Computer Science, ML/AI or Cloud Infrastructure are an asset
• Proven ability translating research concepts into tools, prototypes, or systems considered for real-world use.
• Experience optimizing ML systems and tools for scalability, reliability, and resource efficiency.
• Source Code Analysis: Proficiency in analyzing the source code of AI-based software
• Interest in or exposure to the Trust & Safety landscape and its practical applications

Attributes and Expectations:

• Advanced critical thinking and problem-solving skills
• Strong interpersonal communication skills for effective collaboration with internal teams and external stakeholders. Operates with integrity and trust
• Passion for designing effective learning exercises, technical concept illustrations, training, and evaluation tools
• Ability to manage multiple competing priorities in a fast-paced environment
• Demonstrates professional maturity, resourcefulness, and self-discipline in pursuing organizational goals
• A curious mindset with a keen interest in testing new educational tools and technologies
• Shows presence, self-confidence, sound judgment, and superior problem-solving abilities
• Fosters high-level cross-functional collaboration and establishes credibility while influencing peers to achieve common goals

What you'll love about us

• A professional yet casual work environment that encourages the growth and development of your skills.
• Participate in professional development activities
• Gain access to the Amii community and events
• A chance to learn from amazing teammates who support one another to succeed.
• Competitive compensation, including paid time off and flexible health benefits.
• A modern office located in downtown Edmonton, Alberta.

How to Apply

Were excited to add a new member to the Amii team for this role! We are keeping the door open to new applicants until we find the right fit. When sending your application, please send your CV and cover letter indicating why you think you'd be a fit for Amii. In your cover letter, please include one professional accomplishment you are most proud of and why.

Applicants must be legally eligible to work in Canada at the time of application.

Amii is an equal opportunity employer and values a diverse workforce. We encourage applications from all qualified individuals without regard to ethnicity, religion, gender identity, sexual orientation, age or disability. Accommodations for disability-related needs throughout the recruitment and selection process are available upon request. Any information provided by you for accommodations will be kept confidential and wont be used in the selection process.

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

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.