Job Title: Machine Learning Engineer, New Grad - Quora (Remote) Company: Quora Job Category: Machine Learning Roles & Responsibilities: Responsibilities: * Design, build, and deploy LLM\-powered agents to detect and address spam, harassment, and other policy\-violating content at Quora's scale * Develop agentic workflows to automate complex tasks, improving the efficiency and effectiveness of our content and user moderation systems * Design and improve ML systems that adapt to evolving abuse patterns and new challenges * Evaluate agent performance through offline evaluations, online experiments, and production monitoring, balancing accuracy, reliability, latency, and cost * Investigate failure cases, experiment with new approaches, and iterate on solutions to improve system performance * Identify new opportunities to apply ML and LLMs to content quality and safety across Quora * Collaborate with experienced engineers and take ownership of projects from early development through production Work Location: Canada Availability: Full time

Job Title: Machine Learning Scientist III - Customer Service AI Company: Wayfair Job Category: Machine Learning Roles & Responsibilities: Wayfair is seeking a high\-impact Machine Learning Scientist III to lead the research, technical strategy, and production deployment of next\-generation Generative AI and agentic systems for Wayfair’s Customer Service organization. In this role, you will bridge cutting\-edge AI research and large\-scale enterprise execution—architecting robust, multi\-agent frameworks, proprietary domain\-adapted LLMs, and end\-to\-end LLMOps infrastructure. You will be responsible for defining technical roadmaps, tackling high\-ambiguity customer service challenges, mentoring junior scientists, and collaborating closely with engineering and product leadership. Success requires deep technical mastery of NLP and Generative AI, a demonstrated track record of taking complex AI systems to production at scale, and the executive presence to turn emerging AI capabilities into measurable business ROI and customer lifetime value. Technical Leadership \& Strategy: Help define the Generative AI roadmap and architecture for Customer Service Intelligence, identifying high\-leverage opportunities to deploy agentic workflows, autonomous triage, and real\-time agent copilot systems. Evaluation Frameworks \& Governance: Design rigorous offline and online evaluation ecosystems (LLM\-as\-a\-judge, custom benchmark datasets, semantic observability, red\-teaming) to monitor factual consistency, safety, hallucination mitigation, and task completion in customer\-facing workflows. Cross\-Functional Influence \& Alignment: Serve as the technical authority across product managers, operations directors, legal/compliance, and engineering leaders, translating abstract business challenges into scalable technical implementations with defined ROI metrics. Mentorship \& Engineering Excellence: Set high standards for experimental rigor and code quality across the team; lead design reviews, mentor mid\-level and junior scientists, and foster a culture of rapid, scientifically sound prototyping. Applied Innovation \& Advocacy: Keep Wayfair at the cutting edge by tracking developments in foundation model architectures, context\-caching, vector search, and reasoning models, proactively running proofs\-of\-concept to identify disruptive technology before it commoditizes. Software Engineering \& Infrastructure: Expert\-level software development skills in Python, with clean production code standards, asynchronous programming, containerization (Docker, Kubernetes), distributed training/inference, and modern cloud ML infrastructure (GCP Vertex AI, AWS SageMaker, Azure AI). System Design \& Communication: Exceptional systems\-thinking and stakeholder communication skills, capable of influencing senior cross\-functional leadership, defending trade\-offs in technical design reviews, and explaining complex AI mechanics to non\-technical partners. Work Location: Toronto, Canada Availability: Full time

Job Title: Machine Learning Engineer - Financials 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 Team Do you want to be part of the team which is reinventing Enterprise Financials for the agentic age? The Financials Hyper Automation AI team is a small, advanced team of ML engineers charged with re\-envisioning and building the next generation of ERP Financial and Accounting systems. We have an entrepreneurial mindset with a focus on creating delightful, intelligent experiences, leveraging the state\-of\-the\-art in AI as well as strong, proven techniques from conventional machine learning. Working closely with product managers, we build advanced prototypes as well as deploy full production\-grade features to solve our customer’s most pressing business challenges. Our current areas of development include strong reasoning agents for complex financial workflows and agentic self\-improvement. About The Role As a ML Engineer on the FIN Hyperautomation AI team , you will develop intelligent user experiences powered by advanced tools like (but not limited to) generative AI. You will work with other engineers to deliver ML solutions across Workday’s ML infrastructure, from training ML models to developing APIs, as well as managing the lifecycle of such products and services. You will be backed by Workday’s vast computing resources and rich datasets, to deliver transformative value to our customers. Your specific responsibilities include: * Own exploration, design, implementation, and deployment of features. * The evaluation, scalability, and observability of these features. * Apply ML techniques, including LLMs and natural language understanding, to intelligently process business documents and, for example, automate critical customer workflows. * 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 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: Research Engineer, AI | Ingénieur de recherche en IA Company: Meta Job Category: Machine Learning Roles & Responsibilities: Meta is advancing the frontier of artificial intelligence to power products and experiences used by billions of people worldwide. As a Research Engineer on our AI team, you will work at the intersection of applied AI research and production engineering, implementing and scaling novel machine learning systems that translate cutting\-edge research into real\-world impact. In this role, you will collaborate closely with research scientists to develop, evaluate, and deploy AI models across Meta's family of products, contributing to breakthroughs in areas such as large language models, generative AI, computer vision, and recommendation systems.\-\-\-\-\-\-\-Meta repousse les frontières de l’intelligence artificielle pour alimenter des produits et des expériences utilisés par des milliards de personnes à l’échelle mondiale. En tant qu’ingénieur de recherche au sein de notre équipe d’IA, vous travaillerez à l’intersection de la recherche appliquée en IA et de l’ingénierie de production, en mettant en œuvre et en déployant à grande échelle de nouveaux systèmes d’apprentissage automatique qui transforment la recherche de pointe en retombées concrètes. Dans le cadre de ce poste, vous collaborerez étroitement avec des chercheurs pour développer, évaluer et déployer des modèles d’IA au sein de la famille de produits de Meta, contribuant ainsi à des percées dans des domaines tels que les grands modèles de langage, l’IA générative, la vision par ordinateur et les systèmes de recommandation. Research Engineer, AI \| Ingénieur de recherche en IA Responsibilities: * Implement and optimize machine learning models and AI systems, translating research prototypes into production\-quality, scalable code \| Mettre en œuvre et optimiser des modèles d’apprentissage automatique et des systèmes d’IA, en transformant des prototypes de recherche en code évolutif de qualité production * Design and execute controlled experiments to evaluate model performance, validate research hypotheses, and support data\-driven decisions in collaboration with research scientists \| Concevoir et réaliser des expériences contrôlées pour évaluer les performances des modèles, valider les hypothèses de recherche et appuyer les décisions fondées sur les données en collaboration avec les chercheurs * Build and maintain robust AI pipelines covering data preprocessing, model training, evaluation, and inference at scale \| Concevoir et maintenir des pipelines d’IA robustes couvrant le prétraitement des données, l’entraînement des modèles, l’évaluation et l’inférence à grande échelle * Instrument AI systems with logging, monitoring, and alerting to track model behavior, detect regressions, and ensure production reliability \| Instrumenter les systèmes d’IA avec des fonctions de journalisation, de surveillance et d’alerte afin de suivre le comportement des modèles, de détecter les régressions et d’assurer la fiabilité en production * Identify and resolve performance bottlenecks in model training and inference pipelines to improve latency, throughput, and computational efficiency \| Identifier et résoudre les goulots d’étranglement des performances dans les pipelines d’entraînement et d’inférence des modèles afin d’améliorer la latence, le débit et l’efficacité de calcul. * Collaborate with cross\-functional partners including research scientists, product engineers, and data scientists to define requirements and deliver AI\-powered features \| Collaborer avec des partenaires interfonctionnels, notamment des chercheurs, des ingénieurs de produits et des scientifiques des données, pour définir les exigences et fournir des fonctionnalités alimentées par l’IA * Manage staged rollouts of AI model updates using feature flagging and incremental deployment frameworks, monitoring key metrics throughout \| Gérer le déploiement progressif des mises à jour des modèles d’IA à l’aide de drapeaux de fonctionnalité et de frameworks de déploiement incrémentiel, en surveillant les indicateurs clés tout au long du processus * Contribute to technical documentation for new AI features, experimental findings, and system design decisions to support knowledge sharing across the team \| Contribuer à la documentation technique relative aux nouvelles fonctionnalités d’IA, aux résultats expérimentaux et aux décisions de conception du système afin de favoriser le partage des connaissances au sein de l’équipe. * Follow privacy, security, and responsible AI practices throughout the model development and deployment lifecycle \| Respecter les pratiques en matière de protection de la vie privée, de sécurité et d’IA responsable tout au long du cycle de vie du développement et du déploiement des modèles * Participate in code reviews to improve code quality and share knowledge of AI engineering best practices with peers \| Participer aux revues de code afin d’améliorer la qualité du code et de transmettre aux pairs les connaissances sur les pratiques exemplaires d’ingénierie de l’IA. Work Location: Montreal, Quebec, Canada Availability: Full time

Job Title: Data Architect Company: Manulife Job Category: Machine Learning Roles & Responsibilities: The Data Architect will shape and lead the data architecture strategy that enables trusted, scalable, secure, and AI\-ready data capabilities across the organization. In this role, you will provide technical and architectural leadership across the design, governance, modernization, and implementation of enterprise data solutions and platforms supporting analytics, reporting, machine learning, and AI. You will combine strategic architecture leadership with hands\-on technical expertise, contributing directly to solution design, data platform engineering, and implementation where your expertise can have the greatest impact. Position Responsibilities: * Define and evolve the segment data architecture vision, principles, standards, and roadmap. * Design scalable Data Lake, Data Warehouse, and Lakehouse architectures supporting analytical, operational, and AI workloads. * Establish reusable architecture patterns and standards for data integration, metadata management, data governance, data quality, and data products. * Lead data modernization, migration, and cloud transformation initiatives, helping teams evolve legacy data environments toward modern cloud\-based platforms. * Provide hands\-on technical leadership in the design and implementation of data pipelines, integration frameworks, and cloud\-native data platforms, including data ingestion, transformation, orchestration, and performance optimization. * Design scalable batch, streaming, event\-driven, and near real\-time data processing solutions based on business and technology needs. * Embed data security, governance, privacy, and regulatory requirements into architecture and solution design in partnership with governance, risk, and security teams. * Design AI\-ready data architectures that enable machine learning, advanced analytics, and generative AI solutions. * Provide technical and architecture leadership across strategic data initiatives, including architecture reviews, technology evaluations, solution trade\-offs, and key design decisions. * Collaborate with business stakeholders, architects, engineers, and other technology partners to translate business needs into practical, scalable data solutions. * Experience implementing governed data products, domain\-oriented data architectures, or data mesh concepts in a large enterprise environment. * Experience working in a large, complex, or highly regulated organization, such as financial services, insurance, banking, wealth management, retirement, or another regulated industry. * Familiarity with machine learning, MLOps, and data architectures supporting generative AI solutions. * Working knowledge of DataOps, CI/CD, automation, platform monitoring, performance optimization, and operational resilience for data platforms. * Bachelor's degree in computer science, engineering, information systems, or a related discipline, or equivalent practical experience. * We’ll empower you to learn and grow the career you want. * We’ll recognize and support you in a flexible environment where well\-being and inclusion are more than just words. * As part of our global team, we’ll support you in shaping the future you want to see. The role being advertised is an existing vacancy. Manulife Financial Corporation is a leading international financial services provider, helping people make their decisions easier and lives better. To learn more about us, visit https://www.manulife.com/en/about/our\-story.html. Work Location: Toronto, ON, Canada Availability: Full time

Job Title: Senior Machine Learning Engineer - Content and Contributor Intelligence (Remote - CAN) Company: Yelp Job Category: Machine Learning Roles & Responsibilities: Summary Yelp engineering culture is driven by our values: we’re a cooperative team that values individual authenticity and encourages creative solutions to problems. All new engineers deploy working code their first week, and we strive to broaden individual impact with support from managers, mentors, and teams. At the end of the day, we’re all about helping our users, growing as engineers, and having fun in a collaborative environment. What You'll Do * Conduct end\-to\-end analyses, wrangling data via SQL or Python, to statistical modeling, to hypothesizing and presenting business ideas. * Mentor and guide junior engineers, fostering a culture of learning and technical excellence. * Work with large and complex textual and visual datasets. * Support the development and deployment of projects involving machine learned models for offline, batch\-based data products as well as models deployed to online, real\-time services. * Work in the contributor and visual intelligence team on text and visual understanding, along with fine tuning transformer models to derive embeddings for multiple input types * Productionize and automate model pipelines within Python services. * Drive and advocate adoption of best practices in ML development and operations, and mentor newer engineers in those practices. What It Takes To Succeed * Experience developing and productionizing machine learning models, particularly in neural networks, computer vision and LLMs including their supported data pipelines. * Experience with machine learning using packages such as PyTorch, TensorFlow, Spark MLlib, XGBoost, and Sklearn. * Strong coding skills in Python or equivalent (Java, C\+\+). * Solid understanding of engineering and infrastructure best practices. * The curiosity to uncover promising solutions to new problems, and the persistence to carry your ideas through to an end goal. * We highly value experience of working with LLMs, utilizing LLM APIs (OpenAI, Bedrock, etc), prompt engineering and evaluation. Work Location: Toronto, Ontario, Canada Availability: Full time

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, ON, Canada Availability: Full time

Job Title: Senior Machine Learning Engineer, Premium Discovery Company: Scribd, Inc. Job Category: Machine Learning Roles & Responsibilities: Culture at Scribd, Inc. We support a culture where our employees can be real and be bold; where we debate and commit as we embrace plot twists; and where every employee is empowered to take action as we prioritize the customer. We believe the best work happens when individual flexibility is balanced with meaningful community connection. Scribd Flex empowers employees to choose the workstyle and location that support their best performance, while committing to intentional in\-person moments that strengthen collaboration and culture. Occasional in\-person attendance is required for all Scribd, Inc. employees, regardless of location. So what are we looking for in new team members? At Scribd, Inc., we hire for “GRIT.” Traditionally defined as the intersection of passion and perseverance toward long\-term goals, GRIT reflects the mindset we expect from every employee. For us, it also serves as a practical framework for how we work: setting and achieving Goals, delivering Results within your role, contributing Innovative ideas and solutions, and strengthening the broader Team through collaboration and attitude. Role Overview We're looking for a Senior Machine Learning Engineer to own recommendations for Fable and grow into the technical lead for Premium recommendations. Key Responsibilities * Lead the migration of Fable's recommendations onto Orion, covering data, features, training, serving and experiments, while keeping today's recommendations running. * Extend Orion's rankers, feature store and embedding\-based retrieval to support Fable, in partnership with the Orion ML platform team. * Own the health of Fable's recommendation systems in production: quality, latency, cost and on\-call. * Bring Fable's social signals (shelves, ratings, reviews, book clubs, reader similarity) into recommendations for both Fable and Everand. * Design and analyze A/B tests with product managers and analysts to decide what ships. * Act as technical lead for Premium recommendations. Shape the roadmap with product managers, and see work that depends on other teams' systems through to delivery. * Raise the bar on engineering practice in the squad through design reviews, code quality and operational readiness. Work Location: Vancouver, British Columbia, Canada Availability: Full time

Job Title: Senior Machine Learning Engineer, Premium Discovery Company: Scribd, Inc. Job Category: Machine Learning Roles & Responsibilities: We support a culture where our employees can be real and be bold; where we debate and commit as we embrace plot twists; and where every employee is empowered to take action as we prioritize the customer. We believe the best work happens when individual flexibility is balanced with meaningful community connection. Scribd Flex empowers employees to choose the workstyle and location that support their best performance, while committing to intentional in\-person moments that strengthen collaboration and culture. Occasional in\-person attendance is required for all Scribd, Inc. employees, regardless of location. So what are we looking for in new team members? At Scribd, Inc., we hire for “GRIT.” Traditionally defined as the intersection of passion and perseverance toward long\-term goals, GRIT reflects the mindset we expect from every employee. For us, it also serves as a practical framework for how we work: setting and achieving Goals, delivering Results within your role, contributing Innovative ideas and solutions, and strengthening the broader Team through collaboration and attitude. Role overview ----------------- We're looking for a Senior Machine Learning Engineer to own recommendations for Fable and grow into the technical lead for Premium recommendations. Key responsibilities ------------------------ * Lead the migration of Fable's recommendations onto Orion, covering data, features, training, serving and experiments, while keeping today's recommendations running. * Extend Orion's rankers, feature store and embedding\-based retrieval to support Fable, in partnership with the Orion ML platform team. * Own the health of Fable's recommendation systems in production: quality, latency, cost and on\-call. * Bring Fable's social signals (shelves, ratings, reviews, book clubs, reader similarity) into recommendations for both Fable and Everand. * Design and analyze A/B tests with product managers and analysts to decide what ships. * Act as technical lead for Premium recommendations. Shape the roadmap with product managers, and see work that depends on other teams' systems through to delivery. * Raise the bar on engineering practice in the squad through design reviews, code quality and operational readiness. * Scribd Flex (flexible work model) * Comprehensive health, dental, and vision coverage * Mental health support and disability coverage * Generous paid time off, including vacation, sick time, holidays, winter break, volunteer time, and sabbaticals * Paid parental leave and family support benefits * Retirement matching and employee equity * Learning and development programs and professional growth opportunities * Wellness and home office stipends * Complimentary access to the Scribd, Inc. suite of products * Enterprise access to leading AI tools Work Location: Vancouver, BC, Canada Availability: Full time

Job Title: Machine Learning Engineer Company: Manulife Job Category: Machine Learning Roles & Responsibilities: Manulife's bold ambition is to become a digital, customer\-first leader. To achieve this, we've made significant investments in Advanced Analytics and AI capabilities. This is a global role with exposure to markets in Canada, the U.S., and Asia, offering the opportunity to collaborate with cross\-functional teams and deliver robust, scalable ML systems across multiple business segment Position Responsibilities * Reusable Patterns and Accelerators: Build reusable patterns for data, ML, and GenAI workloads, following MLOps, LLMOps, and AIOps best practices, and partner with delivery teams on implementation. * CI/CD: Own the engineering backbone for ML delivery, including source control workflows, build and deployment pipelines, automated testing, spec\-driven development, and release management. * Infrastructure as Code: Provision and manage PaaS infrastructure using Terraform, with repeatable, version\-controlled environments across development, staging, and production. * Credential and Secrets Management: Implement secure credential handling using Azure Key Vault and managed identities, scoping access narrowly across services and pipelines. * Scalable Infrastructure: Develop and maintain scalable ML platforms and serving infrastructure that support training, inference, monitoring, and lifecycle management of models in production. * Data Pipeline Optimization: Partner with data engineers to build high\-quality, well\-tested feature and training pipelines that ensure efficient, reliable data processing for ML applications. * Model Development and Deployment: Design, train, evaluate, and deploy machine learning models, and integrate large language models where they are the right tool, to solve complex business problems and improve operational efficiency. * Model Performance and Reliability: Continuously monitor and improve models and systems for accuracy, latency, cost, drift, and reliability, with clear observability and alerting. * Governance and Responsible AI: Ensure interoperability, data consistency, and responsible AI through strong API and data standards, metadata management, security\-by\-design, privacy controls, and model governance. * Integration and Collaboration: Partner with data scientists, engineers, and business stakeholders to gather requirements and integrate ML solutions smoothly with existing systems. * Innovation and Research: Stay current with emerging technologies and practices across data engineering, machine learning, and Generative AI, including RAG, vector search, model fine\-tuning, and orchestration frameworks. When You Join Our Team * We’ll empower you to learn and grow the career you want. * We’ll recognize and support you in a flexible environment where well\-being and inclusion are more than just words. * As part of our global team, we’ll support you in shaping the future you want to see. The role being advertised is an existing vacancy. About Manulife And John Hancock Manulife Financial Corporation is a leading international financial services provider, helping people make their decisions easier and lives better. To learn more about us, visit https://www.manulife.com/en/about/our\-story.html. Work Location: Toronto, Ontario, Canada Availability: Full time