Job Title: DSP System Engineer Company: Qualcomm Job Category: Machine Learning Roles & Responsibilities: We are searching for an DSP Systems Engineer* to be part of the Qualcomm AI Processor team responsible for developing DSP software applications and use cases developed for Qualcomm Snapdragon processors. The candidate will work on implementing new cutting\-edge algorithms in the areas of machine learning, computer vision and video processing that bring artificial intelligence to mobile and edge devices. Responsibilities include software design, development, integration, test, and support of these applications for the Qualcomm Hexagon DSP. New Position * Excellent programming skills in C/C\+\+, Python * Strong problem\-solving skills * Knowledge of embedded development * Knowledge of OOP principles * Knowledge of operating system concepts * Knowledge of software development principles and practices * Effective interpersonal communications skill (written and verbal) * Analytical, thorough, resourceful, and detail\-oriented * Self\-motivated, hardworking, and flexible 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 disability\-accomodations@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. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries). If you would like more information about this role, please contact Qualcomm Careers . Work Location: Markham, ON, Canada Availability: Full time

Job Title: Principal Data Scientist (m/f/d) Company: AutoTrader.ca Job Category: Machine Learning Roles & Responsibilities: We are a Canadian leader in digital automotive solutions. Our flagship brands — AutoTrader.ca , AutoSync , Dealertrack Canada and CMS — help Canadians buy, sell, and finance vehicles with confidence. Join our global Data Science team and take a leadership role in shaping the future of the automotive marketplace through cutting\-edge AI and machine learning. As a Principal Data Scientist, you’ll spearhead high\-impact AI initiatives that influence millions of users worldwide, with a focus on both strategic vision and hands\-on innovation. In this role, you’ll collaborate cross\-functionally with product, engineering, and business teams to design, build, and scale AI solutions that set us apart in the industry. You’ll bring deep technical expertise, a passion for innovation, and a strong product mindset to develop ML products that solve real\-world problems and deliver measurable business value. What You’ll Do: * Shape the strategic direction and vision of Data Science across the organization by identifying transformative AI/ML opportunities and championing the team’s evolving role in a rapidly advancing GenAI landscape. * Lead the design and deployment of predictive and generative AI models that power personalization, pricing, search, and optimization in marketplace and fintech domains. * Collaborate with product leaders to align ML initiatives with strategic business goals and drive product innovation through data\-driven experimentation and modeling. * Architect scalable ML infrastructure and automated workflows using cloud\-native tools (e.g., AWS, EC2, Kubernetes) to support efficient model training, deployment, and analytics across diverse datasets. * Ensure long\-term performance and compliance of production AI models though robust governance and monitoring. * Provide technical leadership and mentorship to data scientists, shaping an innovative team culture and fostering high\-performance and continuous learning. * Serve as a cross\-functional technical leader, shaping company\-wide technical initiatives beyond data science. Partner with engineering, product, and platform teams to influence architecture, innovation agendas, and technical standards across the organization. * Act as a senior technical advisor, leading resolution of complex modeling issues and acting as the escalation point for critical incidents. * Lead the exploration and strategic application of GenAI, identifying high\-impact use cases and guiding their integration across products and platforms. What You’ll Need: * Advanced academic credentials in a quantitative field such as Computer Science, Engineering, Mathematics, or related discipline * 10\+ years of experience in data science, machine learning, or applied AI, with a strong portfolio of high\-impact projects in production * Expert\-level programming skills in Python and SQL, and fluency with leading ML/AI frameworks (e.g., scikit\-learn, TensorFlow, PyTorch) * Direct experience with GenAI/LLM technologies, including tools like Hugging Face, LangChain, OpenAI APIs, vector databases, and fine\-tuning methods * Deep knowledge of machine learning algorithms (supervised, unsupervised, deep learning), including model evaluation, explainability, and selection for business\-critical use cases * Strong hands\-on experience with cloud infrastructure (AWS), containerization (Docker), and orchestration (Jenkins, Airflow) * Proven capability in MLOps, including CI/CD pipelines, model monitoring, versioning, and automated retraining * Experience deploying and serving models through APIs (e.g., Flask, FastAPI) in both real\-time and batch\-processing environments * Excellent communication and stakeholder management skills, able to translate complex concepts into actionable insights for non\-technical audiences * Demonstrated success mentoring teams, guiding technical strategy, and advocating for best practices in experimentation, reproducibility, and ethical AI * Experience working in agile product development environments (Scrum/Kanban); experience influencing product roadmaps is a strong plus Experience leveraging AI, Generative AI (GenAI) to enhance engineering productivity, automate repetitive tasks, and optimize workflows. Candidates should demonstrate the ability to integrate AI\-driven solutions into their daily work — such as code generation, debugging, reviews, documentation, and decision support—to improve efficiency for themselves and their teams. A proactive approach to exploring and implementing AI tools that drive innovation and streamline development processes is highly valued* If this opportunity excites you, but you're unsure whether your background checks every box, we value passion, curiosity, and a growth mindset. Reach out and tell us what strengths you would bring to the team. We look forward to hearing from you! Work Location: Toronto, Ontario, Canada Availability: Full time

Job Title: Machine Learning Systems and Infrastructure Developer Company: Siemens Job Category: Machine Learning Roles & Responsibilities: About the role: Are you excited by the engineering work that turns model development into repeatable, governed production rollout? We are seeking a Machine Learning Systems and Infrastructure Developer to build the training infrastructure and model rollout layer for Physical AI. This developer will provision and operate ML environments, automate training and evaluation pipelines, manage model artifacts and registries, and define the promotion path from trained model to validated runtime candidate. The role connects robotics data, partner VLA/RFM work, model evaluation, release gates, and runtime deployment without owning robotics data semantics or the final runtime integration layer alone. * Provision and maintain ML training environments for robotics AI workloads across local, edge, on\-premise, and cloud\-backed infrastructure where applicable. * Build repeatable training, fine\-tuning, evaluation, and model\-packaging pipelines for VLA, VLM, perception, and robot\-learning workflows. * Manage model artifacts, model registries, dataset references, experiment metadata, lineage, approvals, promotion states, and rollback paths. * Automate GPU resource allocation, job scheduling, environment reproducibility, dependency management, and capacity tracking. * Define model rollout workflows from training output to validated runtime candidate, including evaluation gates, release notes, traceability, and operational handoff. * Partner with the Senior AI/ML and Robotics Platform Engineer on dataset readiness, evaluation semantics, and model\-quality criteria. * Partner with ML inference, Edge Runtime, AX integration, QA, and DevOps engineers on packaging, deployment readiness, observability, and release automation. * This role is primarily focused on software and infrastructure, with close collaboration across robotics data, ML research, QA, DevOps, edge runtime, and platform integration teams. * Hybrid work is supported, with on\-site presence expected for training environment setup, model rollout validation, data pipeline integration, and reference\-cell release readiness. * Impact: Build the founding team and platform capability for a strategic Physical AI initiative in Canada. * Innovation: Work at the intersection of robotics, AI, industrial software, workflow orchestration, and platform engineering. * Leadership: Shape the direction, culture, and operating model of a new strategic engineering organization. * Collaboration: Partner with leading global research, product, and engineering teams. * Growth: Help define how Physical AI platform capabilities scale from data foundations to runtime\-enabled industrial applications. Siemens Canada is a leading technology company focused on industry, infrastructure, mobility and healthcare. The company’s purpose is to create technology with purpose, transforming the everyday, for everyone, since 1912\. By combining the real and the digital worlds, Siemens empowers its customers to accelerate their digital and sustainability transformations, making factories more efficient, cities more liveable, and transportation more sustainable. Siemens also owns a majority stake in the publicly listed company Siemens Healthineers, a leading global medical technology provider pioneering breakthroughs in healthcare. For everyone. Everywhere. Sustainably. Work Location: Kitchener, ON, Canada Availability: Full time

Job Title: AI Software Development Engineer in Test Company: Trimble Job Category: Machine Learning Roles & Responsibilities: Shape the Future of Construction AI as an AI Software Developer Engineer in Test! What Makes This Role Great: In this role, you will be at the forefront of implementing cutting\-edge AI testing methodologies and autonomous AI agents, directly accelerating release cycles and transforming product quality across our flagship construction software suite. Key Exciting Responsibilities: * Lead the quality assurance and test execution for new AI components embedded directly into Trimble software. * Design, develop, and adapt custom AI testing tools and automated frameworks to elevate team productivity. * Pioneer and advocate for modern AI test tools, best practices, and automation pipelines across the global QA community. * Implement automated workflows to evaluate and improve software release quality continuously. * Identify and mitigate model biases and risks to guarantee high\-performing AI features. * 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." Software Developer Engineer in Test, SDET, AI Test Engineer, Quality Assurance Engineer, Test Automation, Machine Learning QA, Python, LLM Testing, Model Context Protocol, Construction Technology Work Location: Kamloops, BC, Canada Availability: Full time

Job Title: ML Software Engineer, Routing Company: Lyft Job Category: Machine Learning Roles & Responsibilities: We are hiring a Machine Learning Engineer to join our Routing team. Our team builds and maintains Lyft's system responsible for providing routes for every ride request on our platform. We process millions of route requests per day and low latency, high reliability and high accuracy are paramount for our success. Our technology stack runs on AWS, Kubernetes, Go, Python/C\+\+, Apache Airflow, Flink, and Kafka. We use AI to improve development productivity, optimize customer support workflows, and enhance operational efficiency — all without compromising code quality or security. In this role, you will work with incredibly passionate and talented colleagues from software engineering, machine learning and data science on building rideshare experiences that delight millions of riders and drivers. Responsibilities: * Perform data analysis and build proof\-of\-concept to explore and compare ML and non\-ML solutions * Be able to make effective tradeoffs between model accuracy, its productization complexity and runtime performance * Develop statistical, machine learning, or optimization models * Write production quality code that can scale well to serve millions of requests per day * Participate in code reviews, design reviews, production on\-call support and incident triaging process. * Write well\-crafted, well\-tested, readable, maintainable code Lyft highly values having employees working in\-office to foster a collaborative work environment and company culture. This role will be in\-office on a hybrid schedule — Team Members will be expected to work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in\-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. \#Hybrid Work Location: Toronto, Ontario, Canada Availability: Full time

Job Title: Machine Learning Developer Company: Senstar Job Category: Machine Learning Roles & Responsibilities: Senstar is looking for a Machine Learning Developer to help bring machine learning from research into real\-world applications on embedded edge platforms. This is an opportunity for an early\-career developer who enjoys working with machine learning, software development, automation, and embedded technologies. You'll work closely with an experienced ML researcher, helping build the tools, processes, and workflows that support everything from data collection and model training to optimization and deployment. The role focuses on making machine learning development more efficient, reproducible, and reliable, while providing opportunities to develop hands\-on experience with model optimization and deployment on constrained hardware. Responsibilities * Build and maintain workflows for data collection, labeling, curation, and dataset versioning. * Develop and improve annotation workflows for video, time\-series, and other sensor data using tools such as Label Studio. * Create reproducible training, validation, and testing datasets, maintaining traceability between data, experiments, and model versions. * Automate model training, evaluation, regression testing, and packaging. * Develop tools and processes that improve the efficiency and reliability of machine learning development. * Collaborate with an experienced ML researcher on model training, evaluation, calibration, and optimization. * Support the optimization and deployment of machine learning models to Texas Instruments embedded platforms, including TIDL and related edge inference runtimes. * Analyze and improve inference performance, including latency, memory usage, accelerator utilization, and model accuracy. * Develop Python and C\+\+ tools to integrate, validate, benchmark, and deploy machine learning models. * Embedded systems or edge AI, including Texas Instruments processors and TIDL. * ONNX, model conversion, quantization, pruning, or compression. * Computer vision, signal processing, or time\-series analysis. * Label Studio or similar data annotation platforms. * MLflow, Weights \& Biases, DVC, or similar ML lifecycle tools. * Docker, CI/CD, and automated development workflows. * GPU or hardware\-accelerated inference. Work Location: Waterloo, Ontario, Canada Availability: Full time

Job Title: Applied Machine Learning Scientist Company: Velan Inc. Job Category: Machine Learning Roles & Responsibilities: Velan is a global leader in the design and manufacture of industrial valves. Founded in Montreal, the company is recognized for the quality of its products, its technical expertise, and its human and collaborative corporate culture. As an Applied Machine Learning Scientist, you will develop, deploy, and continuously improve scalable AI/ML solutions that solve meaningful business problems and improve decision\-making, workflow efficiency, and process automation across the organization. Working at the intersection of data science, software engineering, and MLOps, you will transform prototypes into reliable production systems, ensure models remain accurate and trustworthy over time, and collaborate with cross\-functional stakeholders to translate business needs into practical, high\-quality technical solutions. What We Offer Responsibilities * Design, develop, and deploy machine learning models that address high\-value business problems and support scalable process automation. * Build and maintain end\-to\-end ML pipelines, including data ingestion, feature engineering, training, evaluation, deployment, inference, and monitoring. * Convert proof\-of\-concept models into production\-grade solutions that are scalable, robust, performant, and reliable across changing data conditions. * Support the development of autonomous and multi\-agent systems that can reason, plan, execute tasks, and integrate with enterprise tools, databases, APIs, and services. * Monitor deployed models for performance degradation, data drift, bias, and fairness, and retrain or recalibrate models when needed. * Partner with domain experts, engineers, and business stakeholders to define requirements, frame problems, translate objectives into technical solutions, and communicate results clearly. * Apply software engineering best practices, including version control, code review, automated testing, CI/CD, containerization, and orchestration. * Contribute to ML system architecture and technology decisions, ensuring alignment with the company’s data platforms, infrastructure, and technology standards. * Promote strong data and model governance through clear documentation, reproducibility, explainability, and auditability of ML solutions. Qualifications Work Location: Saint-Laurent, Canada Availability: Full time

Job Title: Post-Doctoral Researcher Company: McGill University Job Category: Machine Learning Roles & Responsibilities: Role Overview The Postdoctoral Fellow will develop techniques to build a foundation model of human neurotypes by integrating cognitive task performance, conversational text, and biometric data. The core challenge is utilizing self\-supervised representation learning to construct a continuous latent manifold of individual differences. Responsibilities * Develop tokenization techniques and self\-supervised learning methods to integrate diverse data streams (cognitive results, text, creative choices, psychometrics). * Train models utilizing novel multi\-modal architectures to project qualitative and quantitative data into a unified latent space. * Work closely with a psychometrics postdoc to distinguish genuine cognitive variation from measurement error, device effects, and language confounds. * Design rigorous evaluations focusing on participant\-level data separation, model robustness, missing modalities, and generalization. * Scrutinize models for bias, unsupported sensitive inferences, and stability, ensuring responsible data usage in collaboration with governance bodies. * Collaborate with software engineers on data preprocessing pipelines and model integration within the game's cloud infrastructure. 2026\-11\-30 McGill University hires on the basis of merit and is strongly committed to equity and diversity within its community. We welcome applications from racialized persons/visible minorities, women, Indigenous persons, persons with disabilities, ethnic minorities, and persons of minority sexual orientations and gender identities, as well as from all qualified candidates with the skills and knowledge to productively engage with diverse communities. McGill implements an employment equity program and encourages members of designated groups to self\-identify. Persons with disabilities who anticipate needing accommodations for any part of the application process may contact, in confidence,* accessibilityrequest.hr@mcgill.ca* . Work Location: Montreal, Canada Availability: Full time

Job Title: Senior Analyst, Business Intelligence (12 month Contract) Company: McKesson Job Category: Machine Learning Roles & Responsibilities: Reporting to the Director – Business Intelligence, Supply Chain Analytics COE, the Senior Analyst will use their skills to create business intelligence content in support of McKesson Canada’s largest business segment, the Pharma Distribution businesses. The Senior BI Analyst will collaborate with business analysts and management to build interactive data reports and dashboards to assess the current state of the Pharma Distribution business, identify trends and solve problems. Your role will be to capture requirements, query existing data sources, build data models and BI reports. Key Responsibilities * Interact with management and analysts to define current business problems, capture requirements, and translate these requirements to build data models and measures. * Use Structured Query Language (SQL) to gather and assess data from the reporting database, transactional database, operational data store, and external systems to assist internal and external leadership in decision making. * Provide business intelligence content by creating data models and DAX measures used for data visualization. * Build highly interactive and insightful data visualization reports using MS Power BI. * Implement the use of emerging data analytics technology to foster innovation within McKesson Canada’s supply chain. * Continually assesses data quality throughout the database and coordinates with IT in the correction of source data or creation of translation sources, where applicable. * Continually researches and identify best practices for business data analysis via published literature, formalized training, and professional development efforts. * Communicates and disseminates information about content and how to use Power BI to the various stakeholders. Work Location: Mississauga, Canada Availability: Full time

Job Title: Machine Learning Engineer - Enterprise Company: Boson AI Job Category: Machine Learning Roles & Responsibilities: About the Role: We are seeking a skilled, detail\-oriented, and passionate Machine Learning Engineer to join our enterprise team. In this pivotal role, you will be at the forefront of developing and deploying groundbreaking AI solutions. This involves integrating advanced language/voice/vision models, mastering fine\-tuning techniques, building sophisticated workflows and platforms, and pioneering innovative agentic approaches. You will immerse yourself in challenging problems that demand a deep understanding of model behavior, meticulous implementation, and an unwavering commitment to quality and reliability in enterprise environments. A key and exciting aspect of this role is contributing to the architecture and implementation of intelligent systems where AI agents can perform complex tasks autonomously, interacting with diverse data sources and tools, as we collectively move towards building truly cohesive and powerful AI capabilities for our clients. Responsibilities * Deliver solutions end to end that meet the needs of our customers \- understanding user pain points, scoping product specs, and designing and building LLM\-powered software * Benchmark the model, and help write evals for customers to identify model weaknesses * Develop and deploy modern search systems (e.g., RAG, DeepSearch) to enhance model performance, grounding, and the ability to utilize enterprise\-specific knowledge * Implement and optimize techniques for fine\-tuning and align large models on domain\-specific data * Ensure the quality, reliability, security, and scalability of models and agentic systems through meticulous attention to detail, diligent execution, and continuous monitoring in demanding enterprise settings * Integrate individual AI components into a scalable platform We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Work Location: Toronto, Ontario, Canada Availability: Full time