Job Title: FY27 Intern - Machine Learning AISW Internship - Canada (4 Months) Company: Qualcomm Job Category: Machine Learning Roles & Responsibilities: Qualcomm relentlessly innovates transforming businesses, enriching lives and fortifying societies. Our solutions are pivotal in crafting a smarter, interconnected world. Building on our nearly 40\-year history of era\-defining technology breakthroughs, we deliver leading\-edge AI, high performance, lower\-power computing, and unrivaled connectivity. We’re proud to be the partner of choice to many of the world’s largest enterprises. Together with our ecosystem partners, we enable next\-generation digital transformation. At Qualcomm, we are engineering human progress. Our internship hiring model routes candidates from this application into multiple project specific roles. Your "Profile Visibility" choice will guide how we manage your data across our systems. To be considered for the full breadth of internship opportunities, select the option to use your profile data for "Any Roles Globally". If you choose to limit your data to "Only The Role I'm Applying For", it will restrict the opportunity for you to be considered across matching internship opportunities. Role Overview Responsibilities may include: * Build software tools for profiling and debugging to accelerate the deployment of new neural networks in this rapidly evolving field. * Enhance AI system performance to maximize the potential of Qualcomm’s hardware and software platforms. * Adapt state\-of\-the\-art neural network models for real\-world customer applications on Qualcomm’s hardware and software platforms. * Optimize algorithms for machine learning operators and layers within the Qualcomm AI software stack. Maintain, enhance, and develop testing infrastructure and automation to support, validate, and enable AI/ML backend features, ensuring reliability, scalability, and high\-quality deployment. * Our interns join world\-class teams to help define and build what is next for mobility and the world. You’ll be paired with a mentor with visibility to your project and team, receive support from your manager, and have access to the entire Qualcomm employee community to ensure your success. To round out your internship, we host professional development workshops, social events, cross\-functional speaker sessions, and an executive speaker series. In addition to competitive hourly pay and accrued vacation time, you will receive housing stipend to accommodate for the duration of your internship. This role may require an export license for candidates with citizenship in certain countries (see current country list below – subject to change). Qualcomm, like other companies, is experiencing significant delays in the export license process. Please be advised that if an export license is required, you may not be able to start work with Qualcomm until the license is granted, which may impact your ability to participate in the internship. Applicants : Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e\-mail myhr.support@qualcomm.com or call Qualcomm's toll\-free number found here . Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. If you would like more information about this role, please contact Qualcomm Careers . Work Location: Markham, Canada Availability: Full time

Job Title: Software Developer II (Full Time) - Canada Company: Cisco Job Category: Machine Learning Roles & Responsibilities: Please note this posting is to advertise potential job opportunities. This exact role may not be open today but could open in the near future. When you apply, a Cisco representative may contact you directly if a relevant position opens. You would play a crucial role in driving next\-gen software innovations including cloud, mobile, desktop or security spaces. On any of these teams, you'll get hands\-on experience working with applications that make technology accessible no matter what device they're on. See the possibilities when creativity meets develop and build solutions which will transform how we work, live, learn, and play. As a software developer on our team, you will be the driving force behind crafting user\-friendly, reliable software and tools that support critical technology platforms such as operating systems, networks, and databases. You will balance growing our software capabilities with hardware compatibility considerations and have the opportunity to influence develop decisions. We offer diverse opportunities across Applications Development, Database Development, Embedded Networking and OS Development, IT, Security, Test\& Quality, and Web Services. You are a collaborative communicator with strong organizational skills and a passion for solving sophisticated challenges. Driven and resourceful, you excel at managing your time efficiently, streamlining processes, and delivering high\-quality results on schedule. Join us to apply your problem\-solving skills and contribute to innovative software solutions that make a significant impact. For non\-sales roles, employees are also eligible to earn annual bonuses subject to Cisco’s policies. Work Location: Ottawa, ON, Canada Availability: Full time

Job Title: Research Associate (Lab Technician / Research Scientist – Turnkey Systems) Company: University of Regina Job Category: Machine Learning Roles & Responsibilities: Position Overview The position will focus on designing, developing, and integrating turnkey sensing systems across the full electronics and mechanical lifecycle—from multilayer PCB design and microcontroller programming to graphical user interface (GUI) development and mechanical CAD modelling (AutoCAD, Fusion 360, SolidWorks)—with a strong emphasis on mechatronics and swarm\-based unmanned systems. The role involves system\-level integration of IoT connectivity, embedded systems, and diverse AI/ML techniques for sensor platforms, alongside the design, prototyping, and field validation of UAVs and drones for land, water, and air operations. The incumbent will contribute to swarm design, including multi\-agent coordination, cooperative sensing, communication architectures, formation control, path planning, and decentralized autonomy for UAVs, UGVs, USVs, and hybrid/amphibious platforms. They will also manage project budgets, procurement, vendors, and deliverables for funded research projects, and support field validation, documentation, and training of junior personnel. High\-performing candidates may have the opportunity to transition into a job\-embedded PhD after 6–12 months, allowing them to pursue doctoral studies while continuing their full\-time research and development work at the University. Responsibilities: * Design and develop multilayer PCBs for sensor interfacing, signal conditioning, data acquisition, and power management using industry\-standard EDA tools (e.g., Altium, KiCad, Eagle). * Develop intuitive graphical user interfaces (GUIs) using Qt, PyQt, LabVIEW, or web\-based dashboards for real\-time data visualization, remote system control, and end\-user interaction. * Lead system\-level design integration, ensuring seamless interaction between sensing materials, analog front\-ends, digital processing units, communication modules, and power subsystems. Implement IoT connectivity (Wi\-Fi, Bluetooth, LoRaWAN, Zigbee, cellular, MQTT, HTTP/REST) and integrate AI/ML algorithms for on\-device sensor data processing, including: * + Edge AI: TensorFlow Lite Micro, CMSIS\-NN, or similar frameworks for real\-time inference on microcontrollers. + Predictive Analytics: Time\-series forecasting (LSTM, GRU, Prophet) for predictive maintenance and environmental trend analysis. + Anomaly Detection: Isolation Forest, Autoencoders, or One\-Class SVM for identifying outliers and sensor faults. + Classification: Support Vector Machines (SVM), Random Forest, Gradient Boosting (XGBoost, LightGBM), and Neural Networks for pattern recognition and event detection. + Regression Models: Linear/Polynomial Regression, Ridge, Lasso, and Gaussian Process Regression for sensor calibration and concentration prediction. + Unsupervised Learning: K\-Means, DBSCAN, and PCA for clustering and dimensionality reduction of high\-dimensional sensor data. + Reinforcement Learning: Application of RL for adaptive sensor control and optimization of system parameters. + Deep Learning: CNNs for spectrogram/image analysis and RNNs/LSTMs for sequential data processing. + Generative AI: GANs or VAEs for synthetic data generation to augment limited training datasets. * Manage project budgets, track procurement processes, coordinate with external vendors and subcontractors, and ensure timely delivery of project milestones and deliverables for funded research initiatives. * Maintain laboratory inventory, electronic components stock, equipment calibration schedules, and safety compliance for electronics prototyping and fabrication workstations. * Support technology demonstrations for academic researchers, industry representatives, government partners, and prospective commercialization stakeholders. * Familiarity with MLOps practices for continuous integration, deployment, and monitoring of machine learning models in production environments. * Research statement (1–2 pages) – Describe your past contributions and future research vision in the development of turnkey systems and sensing. Safety Statement The University is committed to maintaining a safe and healthy workplace and strengthening a culture of safety across the campus community. All employees share responsibility for contributing to a safe working environment. Work Location: Regina, Sikkim, Canada Availability: Full time

Job Title: Research Associate (Lead Scientist - Turnkey Systems) Company: University of Regina Job Category: Machine Learning Roles & Responsibilities: The position will focus on designing, developing, and integrating turnkey sensing systems across the full electronics and mechanical lifecycle—from multilayer PCB design and microcontroller programming to graphical user interface (GUI) development and mechanical CAD modelling (AutoCAD, Fusion 360, SolidWorks). The role involves system\-level integration of IoT connectivity, embedded systems, and diverse AI/ML techniques for sensor platforms, while also sitting at the core of mechatronics and swarm systems engineering for UAVs and drones operating across air, land, and water, including unmanned aerial, ground, surface, and amphibious/aerial\-aquatic platforms. Responsibilities encompass mechatronic subsystem design—actuation, propulsion, control, power, and sealing/waterproofing—as well as swarm design—formation control, task allocation, decentralized autonomy, inter\-agent communication, and collaborative sensing—alongside architecting scalable hardware/software stacks for individual and swarm operations across domains, developing multi\-domain sensor suites such as LiDAR, cameras, IMU/GNSS, radar, sonar, and environmental/payload sensors, implementing AI/ML for perception, sensor fusion, SLAM, object tracking, path planning, and multi\-agent decision\-making, and building embedded/IoT stacks including microcontrollers, ROS/ROS2, MAVLink, MQTT, edge computing, and GUI dashboards. The engineer will also perform mechanical CAD, prototyping, waterproofing, buoyancy, thermal, and vibration validation for air, land, and water platforms, and manage project budgets, procurement, vendors, and deliverables for funded research projects. Responsibilities: * You will be leading a dynamic team tof 3 engineers/technitions and students. * Design and develop multilayer PCBs for sensor interfacing, signal conditioning, data acquisition, and power management using industry\-standard EDA tools (e.g., Altium, KiCad, Eagle). * Develop intuitive graphical user interfaces (GUIs) using Qt, PyQt, LabVIEW, or web\-based dashboards for real\-time data visualization, remote system control, and end\-user interaction. * Lead system\-level design integration, ensuring seamless interaction between sensing materials, analog front\-ends, digital processing units, communication modules, and power subsystems. * Implement IoT connectivity (Wi\-Fi, Bluetooth, LoRaWAN, Zigbee, cellular, MQTT, HTTP/REST) and integrate AI/ML algorithms for on\-device sensor data processing, including: + Edge AI: TensorFlow Lite Micro, CMSIS\-NN, or similar frameworks for real\-time inference on microcontrollers. + Predictive Analytics: Time\-series forecasting (LSTM, GRU, Prophet) for predictive maintenance and environmental trend analysis. + Anomaly Detection: Isolation Forest, Autoencoders, or One\-Class SVM for identifying outliers and sensor faults. + Classification: Support Vector Machines (SVM), Random Forest, Gradient Boosting (XGBoost, LightGBM), and Neural Networks for pattern recognition and event detection. + Regression Models: Linear/Polynomial Regression, Ridge, Lasso, and Gaussian Process Regression for sensor calibration and concentration prediction. + Unsupervised Learning: K\-Means, DBSCAN, and PCA for clustering and dimensionality reduction of high\-dimensional sensor data. + Reinforcement Learning: Application of RL for adaptive sensor control and optimization of system parameters. + Deep Learning: CNNs for spectrogram/image analysis and RNNs/LSTMs for sequential data processing. + Generative AI: GANs or VAEs for synthetic data generation to augment limited training datasets. * Manage project budgets, track procurement processes, coordinate with external vendors and subcontractors, and ensure timely delivery of project milestones and deliverables for funded research initiatives. * Maintain laboratory inventory, electronic components stock, equipment calibration schedules, and safety compliance for electronics prototyping and fabrication workstations. * Support technology demonstrations for academic researchers, industry representatives, government partners, and prospective commercialization stakeholders. * Familiarity with MLOps practices for continuous integration, deployment, and monitoring of machine learning models in production environments. Safety Statement The University is committed to maintaining a safe and healthy workplace and strengthening a culture of safety across the campus community. All employees share responsibility for contributing to a safe working environment. Work Location: Regina, Sikkim, Canada Availability: Full time

Job Title: Senior/Lead Machine Learning Engineer Company: Mimica Job Category: Machine Learning Roles & Responsibilities: We’ve raised $26 million in Series B financing and are scaling fast. Backed by investors including Khosla Ventures and Paladin Capital, our proprietary AI technology is trusted by Fortune 500 companies to accelerate transformation. Mimica is recognized as a Top 100 AI Start\-up by Accel and an industry Leader by the Everest Group. Behind our platform is a team of exceptionally talented people, remote\-first and globally distributed across 16\+ countries. We're looking for curious, collaborative people excited to solve complex problems. You'll join a fast\-paced environment built on high ownership, bottom\-up thinking, and transparent, open communication – helping some of the world's leading organizations transform the way work gets done with AI. * We prioritize customer needs first * We work in small, project\-based teams * We have flexibility in terms of the problems we work on * We own the full lifecycle of our projects * We avoid silos and encourage taking up tasks in new areas * We balance quality and velocity * We have a shared responsibility for our production code * We each set our own routine to maximize our productivity * Own, debug, and improve production pipelines for accuracy and efficiency. * Design, build, and iterate on LLM evals and LLM\-as\-a\-judge systems, including the datasets, metrics, and benchmarks to monitor quality. * Run rigorous experiments on prompts, pipeline design, model choice, and inputs (e.g., OCR text vs. image \+ OCR), and turn the results into clear recommendations. * Drive LLM efficiency improvements across our pipelines by comparing models, restructuring steps, and replacing LLM calls with smaller, purpose\-built models where it makes sense. * Expand our anonymization pipeline, including evaluating and adapting existing models. * Work with Python and quality engineers to take experiments into production, and share responsibility for the code you ship. * Document findings in writing (eg. experiment reports, design docs) Annual learning \& development budget Work Location: Montréal, QC, Canada Availability: Full time

Job Title: Firmware & Machine Learning Engineering Intern (16 Months) Company: Trimble Job Category: Machine Learning Roles & Responsibilities: What Makes This Role Great: In this role, you will be at the forefront of implementing cutting edge machine learning algorithms directly into navigation firmware, directly influencing system performance and shaping the future of autonomous positioning technology. Key Exciting Responsibilities * Take part in machine learning development activities related to Trimble Applanix APX/AP\+ firmware. * Drive critical engineering activities including debugging, data analysis, and algorithm implementation for real\-time systems. * Develop software using industry standard development tools such as GIT and JIRA within an agile team framework. * Collect, structure, and organize high quality datasets to power continuous navigation model improvements. * Produce comprehensive technical documentation to support system level integration and ongoing development. * Knowledge of system level integration and multi\-component hardware/software development. * Proven ability to multi\-task effectively in a dynamic, highly agile environment. * Strong presentation skills and ability to communicate technical findings clearly. * You'll work on projects that truly matter: Our purpose\-driven culture means you'll be helping to build and deliver solutions that make work faster, safer, and more sustainable for millions of people worldwide. Our impact is tangible, from connected machines that save fuel to data\-driven insights that reduce waste. * Collaborate with like\-minded people: Our strong internal culture is a "hidden gem." You will work with a collaborative, supportive team that shares your purpose and fosters a genuine sense of belonging. We're a company of "visionary pragmatists" who think boldly and build things that work. * Be an owner: Trimble thrives on individuals who take initiative and embrace ownership. You'll find an entrepreneurial spirit where success is often "self\-authored," empowering proactive "doers." Navigation Engineering, Machine Learning Intern, TinyML, Kalman Filtering, C\+\+, Python, Linux, Firmware Development, MCU, Applanix Work Location: Richmond Hill, ON, Canada Availability: Full time

Job Title: Manager, ML Engineer Company: RBC Job Category: Machine Learning Roles & Responsibilities: Job Description Reporting to the Director, Credit \& Stress Testing Implementation Assurance, the Manager, ML Engineer will apply business and technical knowledge to turn models into production\-grade services that will support model development across the Credit Modeling and Methodology Team (CMM). In this position you will have the opportunity to work across all banking book exposures in full development/deployment cycles of critical provisioning (CECL, IFRS9\) and stress testing (CCAR, EWST, MST) programs. You will be responsible for the production lifecycle of the ECL generation process through development of production source code, building and execution of user assurance and post\-implementation testing (UAT/PIV), writing implementation documentation, and development of continuous assurance solutions. Develop credit risk model implementations* * Develop scalable and efficient production implementations of all credit risk models across provisioning and stress testing programs * Engineer and maintain scalable ETL pipelines and workflows * Apply and advocate for coding best practices to optimize production system performance, scalability, and reliability * Development of scalable testing solutions to increase coverage, including unit testing * Build and maintain CI/CD automation (Docker, Kubernetes, OpenShift, GitHub Actions, Airflow) * Contribute to code reviews, collaborate with data scientists, credit risk modelers, and IT teams * Maintain technical documentation and submit change control UAT/PIV evidence for validation review * Use of quantitative methods to diagnose model implementation issues and impacts * 0\-2\+ years related work experience in developing and/or deploying scalable coding solutions (including distributed systems and performance optimization) * Knowledge of credit risk methodology, including capital estimation, credit risk/stress testing models, and/or direct experience with Expected Credit Loss implementations + Strong programming experience and providing technical leadership on modern Python and PySpark (or similar) * + Experience in data manipulation on large datasets * Credit Risk \& Banking Stress Testing: Understanding of provisioning models and stress testing frameworks * Testing \& QA: UAT/PIV testing experience in regulated financial environments * Experience in code management solutions (e.g. Git, GitHub) + Strong interpersonal, communication, and presentation skills, with the ability to articulate and document complex technical problems and control process for a non\-technical audience + Ability to structure workload and manage multiple competing priorities. + Conceptual thinker with a curious mind to challenge and question the status quo and the ability to make quantitative decisions on ambiguous and complex techniques which will have an impact directly on RBC’s financial statements. * A comprehensive Total Rewards Program including bonuses and flexible benefits and competitive compensation * Leaders who support your development through coaching and managing opportunities * Ability to make a difference and lasting impact * Flexible work/life balance options * Work in a dynamic, collaborative, progressive, and high\-performing team * Opportunities to do challenging work Code Reviews, Communication, Critical Thinking, Financial Instruments, Financial Regulation, GitHub, Long Term Planning, Process Management, Python (Programming Language), Quantitative Methods, Risk Management, Source Code ManagementAdditional Job Details GROUP RISK MANAGEMENTJob Type: At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC. We believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all. Work Location: Toronto, ON, Canada Availability: Full time

Job Title: Senior Machine Learning Engineer - AI Platform Company: Workday Job Category: Machine Learning Roles & Responsibilities: Your work days are brighter here. We’re obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we’re shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you’ll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We’re in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun\-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you’ll do meaningful work with Workmates who’ve got your back. In return, we’ll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you’ve found a match in Workday, and we hope to be a match for you too. About The Role As a Machine Learning Engineer on the AI Core team, you will develop tailored user experiences using advanced Agentic AI, LLMs and RAG. You will collaborate with other engineers to deliver ML solutions across Workday’s product ecosystem and use current software and data engineering stacks to enable training, deployment, and lifecycle management of a variety of ML models; supervised and unsupervised. Additionally, you will develop and deploy new APIs/services using Docker/Kubernetes at scale and leverage Workday’s vast computing resources on rich datasets to deliver transformative value to our customers. Sound like your kind of challenge? You are a strong technical leader with deep Python expertise and solid software engineering skills, capable of writing beautiful, well\-designed code while delivering solutions efficiently. Specifically, you will: * Own exploration, design and implementation of features for our sophisticated ML platforms, pipelines and services. * Be responsible for evaluation, scalability and observability of these features. * Apply machine learning techniques including LLMs and natural language understanding to analyze large sets of HR and Finance\-related text data, and design and launch pioneering cloud\-based machine learning architectures * Stay up to date with advancements in AI, LLMs, RAG, autonomous agents and orchestration frameworks to drive innovation * Serve as a technical role model for more junior engineers Other Qualifications: * 3\+ years of experience in building information retrieval systems and/or graph\-based recommendation systems. * 3\+ years of hands\-on professional experience in developing large language models (LLMs), text generation models, or graph\-based machine learning models for production, including data processing, model fine\-tuning, model deployment and model evaluation * 3\+ years of experience building services to host machine learning models in production at scale * 3\+ years of experience in machine learning and deep learning frameworks \& toolkits such as PySpark, Pytorch, TensorFlow, and Sklearn * 3\+ years of professional experience with data engineering and data wrangling using e.g. Pandas and PySpark and other industry tools used to build scalable machine learning systems, such as Kubernetes and Docker * Deep understanding of statistical analysis, unsupervised and supervised machine learning algorithms, and natural language processing for information retrieval and/or recommendation system use cases * Professional experience in independently solving ambiguous, open\-ended problems and technically leading teams * Ability to communicate clearly and effectively in a cross\-functional setting with product managers, app teams, and leadership The application deadline for this role is the same as the posting end date stated as below: Our Approach to Flexible Work With Flex Work, we’re combining the best of both worlds: in\-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in\-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter. Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process! At Workday, we value our candidates’ privacy and data security. Workday will never ask candidates to apply to jobs through websites that are not Workday Careers. Work Location: Vancouver, British Columbia, Canada Availability: Full time

Job Title: Senior ML/AI Engineer Company: Canadian Tire Corporation Job Category: Machine Learning Roles & Responsibilities: What You'll Do * Develop a deep understanding of our Retail business, Loyalty program, and how personalized offers are composed and delivered across our retail banners. * Design and deliver offline evaluation frameworks with explicit success criteria — ranking metrics, held\-out AUC, time\-respecting splits, and point\-in\-time correctness — so that an offline win reliably predicts online lift. * Research and apply modelling methodology to select (and justify) the right approach for a given business problem, from matrix factorization and two\-tower retrieval to learning\-to\-rank and sequential architectures. * Build and optimize large\-scale feature engineering in PySpark over hundreds of millions of transaction records, with the profiling skills to know why a job is shuffling. * Design and operate our ML platform layer — feature store, reproducible training pipelines, and cloud training job submission — so retraining is cheap and routine rather than a project. * Design and implement agentic AI solutions that automate model improvement — extending our in\-house harness where an AI agent proposes changes, scores them against a locked benchmark, and keeps only what measurably helps, under human review. * Lead optimization and orchestration of end\-to\-end analytical pipelines across multiple data sources and modelling workstreams to ensure scalability and production reliability. * Raise the engineering standard of the team through code review, documentation, and mentorship of engineers working adjacent to the model layer. What You Bring * B.S or M.S, preferably in Computer Science/Statistics/Math/Engineering or a related quantitative discipline. PhD an asset. * 3\+ years experience developing and deploying machine learning solutions in production — owning data, training, evaluation, release, and operational support. Experience in retail, loyalty programs, personalization, or ad\-tech ranking preferred. * Expert\-level Python, writing production\-grade ML code rather than notebooks handed off for deployment. * 4\+ years of experience querying and analyzing large datasets with tools such as SQL and Spark, with demonstrated depth in PySpark. * Demonstrated experience with recommender systems or large\-scale ranking, and the judgment to know which technique a problem actually requires. * Rigorous approach to offline evaluation — including train/validation splits that respect time, point\-in\-time correct feature construction, and leakage you have personally found and fixed. * Experience with deep learning frameworks (PyTorch, TensorFlow) and gradient boosting libraries such as LightGBM or XGBoost. * Production experience with a major cloud ML platform — Vertex AI preferred; SageMaker or Azure ML acceptable — including custom training jobs, artifact management, and cost control. Familiarity with BigQuery and cloud\-based data structures is an asset. * Experience designing and orchestrating multi\-stage analytical pipelines with workflow optimization, preferably Apache Airflow at production scale. * Familiarity with agentic AI architectures, LLM\-based solutions, and working fluently with coding agents is a strong asset. Infrastructure\-as\-code experience (Terraform) and cloud IAM familiarity is an asset. * Excellent oral and written communication skills, with the ability to communicate both technical and business concepts, as well as strong presentation skills. * Demonstrated ability to work independently with minimal supervision, effectively navigating and resolving ambiguous problems and situations. About Us Canadian Tire Corporation, Limited (“CTC”) is one of Canada’s most admired and trusted companies. With more than 90 Owned Brands, over 1,600 retail locations, financial services, exemplary e\-commerce capabilities, and exciting market\-leading merchandising strategies. We dream big and work as one to innovate with purpose for our customers at every level of our business, investing in new technologies and products, and doubling down on top talent to drive the company forward. We offer competitive salaries and wages to CTC employees, as well as store discounts, supported learning through our Triangle Learning Academy, Canadian Tire Profit Sharing, and retirement and savings programs for eligible employees. As part of our enhanced flex benefits program, we offer mental health benefits in the amount of $5,000 per year for benefits\-eligible employees and their families, including total well\-being, and mental health tools and resources for all employees. Join us in helping to make life in Canada better through living and working our Core Values: we are innovators and entrepreneurs at our core, outcomes drive us, inclusion is a must, we are stronger together and we take personal responsibility. It is an especially exciting time to join CTC and its family of companies where career opportunities are wide\-ranging! Join us, where there's a place for you here. Work Location: Toronto, Ontario, Canada Availability: Full time

Job Title: Winter 2027: Sessional Lecturer: LMP1210H: Basic principles machine learning biomedical research Company: University of Toronto Job Category: Machine Learning Roles & Responsibilities: Department: Dept of Lab. Medicine \& Pathobiology Estimated TA support: not applicable Description of duties: Preparation and delivery of course content, including lectures and/or seminars; creation of courseware; the development and administration of assignments, tests and examinations; marking and grading of student work and the submission of grades to appropriate University officials, maintenance of reasonable hours of student contact outside of scheduled contact hours. Creation, maintenance and management of the Quercus site for the course, collecting material from the lecturers in advance and posting lecturer slide sets (power points), handouts, reading lists, journal articles and bibliographies and preparing other course content as required. The University of Toronto has implemented a process to substantiate Indigenous Membership/Citizenship/Enrolment for candidates who identify as Indigenous. For more information about this process, please refer to the* Indigenous Substantiation Website.* Work Location: Toronto, Canada Availability: Full time