Job Title: Principal Data & AI Engineer Company: General Dynamics Mission Systems Job Category: Machine Learning Roles & Responsibilities: Job Description GDMS\-I is establishing an enterprise Data \& AI capability to support digital transformation, advanced analytics, automation, and artificial intelligence initiatives across the organization. As GDMS\-I increases its investment in AI, a robust enterprise data foundation is required to ensure information is accessible, trusted, secure, and ready to support advanced analytics and AI\-enabled business processes. The Principal Data \& AI Engineer will be responsible for establishing and maturing our enterprise data engineering capability, defining architecture and integration patterns, and leading the implementation of our strategic data platform. The role will lead the development of scalable data pipelines, integration frameworks, cloud\-based data platforms, and AI data services that enable business intelligence, automation, and future AI capabilities across the enterprise. Key Responsibilities * Establish and oversee enterprise data platforms leveraging Microsoft Azure, Snowflake, and MuleSoft. * Define the strategy for scalable, reusable, and governed data pipelines for ingesting, transforming, and integrating enterprise data from business systems, engineering platforms, and external sources. * Architect the enterprise integration services and APIs using MuleSoft and modern integration patterns. * Lead the implementation of cloud\-native data architectures, including data lakes, data warehouses, and semantic data models. * Establish data engineering standards, design patterns, and best practices to support enterprise scalability and long\-term sustainability. * Manage the prioritization of data products that enable business intelligence, reporting, analytics, automation, and AI initiatives. * Enable AI and machine learning use cases by ensuring high\-quality, accessible, and governed enterprise data. * Direct the adoption of Retrieval\-Augmented Generation (RAG), vector search, knowledge retrieval, and AI integration capabilities where appropriate. * Define the direction for and manage real\-time and event\-driven data processing solutions. * Establish requirements and oversight for monitoring, observability, data quality, metadata management, and governance controls across enterprise data platforms. * Collaborate with business stakeholders, application teams, architects, and technology partners to identify and deliver data solutions that address business priorities. * Lead the development and execution of GDMS\-I's enterprise Data \& AI strategy and roadmap. * Bachelor’s degree in computer science, Engineering, Data Science, Information Systems, or related discipline, or demonstrable equivalency in experience. * 8\+ years of experience in data engineering, systems integration, software engineering, or related technical disciplines. * Demonstrated experience establishing and maturing enterprise\-scale data platforms and integration solutions. * Strong experience with Azure cloud services, including data, analytics, and AI\-related services. * Experience developing and supporting Snowflake\-based data platforms. * Hands\-on experience with MuleSoft or equivalent enterprise integration platforms. * Strong development experience with SQL, Python, APIs, and data orchestration technologies. * Strong understanding of data architecture, data modeling, data governance, security, and metadata management. * Experience supporting analytics, reporting, machine learning, or AI\-enabled solutions. * Ability to operate independently in a highly technical, hands\-on engineering role. * Experience with Microsoft Fabric, Azure Data Factory, Synapse Analytics, Azure AI, Azure OpenAI, and related Microsoft data services. * Experience implementing RAG architectures, vector databases, AI agent frameworks, and large language model integrations. * Experience with data cataloging, master data management, and enterprise information governance. As a full\-time employee at General Dynamics Mission Systems–Canada, you’ll enjoy a competitive total rewards package that supports your professional and personal well\-being: We reserve the right to close this vacancy early if we receive sufficient applications for the role. Therefore, if you are interested, please submit your application as early as possible. Work Location: Ottawa, ON, Canada Availability: Full time
Job Title: Machine Learning Engineer Company: Zurich Canada Job Category: Machine Learning Roles & Responsibilities: Are you looking for a caring, collaborative, values\-driven workplace with inspiring teammates and leaders? Do you have the ambition and desire to be the best and thrive at the most impactful global insurance provider in the world? Look no further than Zurich Canada. Zurich Canada is expanding its AI Engineering capability and is looking for Machine Learning / AI Engineers to design, develop and operationalize scalable AI and machine learning solutions. What you will do Machine Learning Engineer \- Applied AI * Build/productionize predictive ML/AI: classification, regression, forecasting and clustering. * Build feature pipelines; establish training, validation/testing and bias/fairness testing. * Evaluate models; move experiments to production and optimize inference. * Assess approved A/B, shadow or controlled pilots; monitor data quality, performance/drift and troubleshoot production issues. * Document assumptions, limitations, versions, training\-data references and approvals. Machine Learning Engineer \- Generative AI * Engineer, evaluate and productionize enterprise GenAI using foundation models, retrieval and agentic patterns. * Build LLM services and RAG pipelines covering ingestion, parsing, cleaning, chunking, embeddings, indexing/retrieval. * Evaluate keyword, semantic\-vector/hybrid search, filtering/reranking; design prompts, structured outputs/context management. * Improve groundedness through retrieval quality, grounding checks, citations, abstention and human review. * Build controlled agentic workflows/tool integrations; evaluate retrieval, answers, safety, agent behaviour/business outcomes. * Monitor quality, groundedness, safety, latency, reliability/cost; apply access\-aware retrieval, sensitive\-data controls and prompt\-injection defences. * Maintain auditable model, prompt, data, index and evaluation records. Machine Learning Engineer \- Data \& ML Platforms * Build/operate enterprise\-scale data, feature and engineering foundations for ML/AI. * Develop training and batch/real\-time inference pipelines, reusable feature frameworks and batch/streaming components. * Optimize Spark/distributed processing; build secure data\-platform/AI interfaces and reusable libraries/templates. * Implement ML dataset quality monitoring; support feature management, lineage/reproducibility. * Engineer large\-scale structured/unstructured data; deploy, monitor and troubleshoot production ML data pipelines. MLOps Engineer * Build/operate platforms, automation and controls across the ML/AI lifecycle. * Design CI/CD for models/AI applications; establish model registration, versioning, lineage/promotion. * Build reproducible training/deployment environments; support staged releases, shadow deployments/rollback. * Monitor health, latency, data quality, model performance/drift; develop retraining/redeployment workflows with validation/approvals. * Manage ML infrastructure/configuration; implement access controls, audit trails/governance evidence and reusable MLOps standards. * Python and SQL skills. * Software engineering fundamentals including Git, APIs, testing and CI/CD. * Understanding of ML concepts and the model\-development lifecycle. * Experience with data processing and analytical workloads. * Experience in cloud\-based development environments. * Understanding of reliable, maintainable, production\-ready solutions. * Databricks, MLflow and Apache Spark/PySpark. * Microsoft Azure or equivalent AWS/Google Cloud technologies. * Azure DevOps or GitHub. * Docker and containerized applications. * REST APIs. * scikit\-learn, PyTorch, TensorFlow or comparable ML/deep\-learning frameworks. * Azure OpenAI or comparable managed AI platforms. * RAG, embeddings, retrieval and LLM evaluation. * Infrastructure as code, Kubernetes and production observability. * Security, privacy, Responsible AI and model governance in a regulated environment. Intermediate * Independently design/deliver ML/AI components and solutions. * Own development through production implementation. * Make appropriate engineering and technology choices. * Troubleshoot complex data, model and production issues. * Contribute to architecture and engineering standards. * Mentor junior team members. * Work with stakeholders to refine technical requirements. Senior * Lead design/engineering of complex enterprise AI/ML solutions. * Make architecture and technology decisions. * Establish reusable patterns and engineering standards. * Lead production\-readiness, scalability, reliability and security decisions. * Mentor engineers and provide technical leadership. * Drive engineering excellence through design/code reviews. * Partner with architecture, security, governance and business leadership. * Evaluate emerging AI technologies and appropriate enterprise adoption patterns. We value diverse perspectives and foster a collaborative environment where employees are empowered to make an impact. We offer a comprehensive rewards package designed to support employee well\-being, growth, and success. * Comprehensive health and wellness benefits. * Minimum four weeks of vacation annually. * Four personal days each year to support personal, cultural, religious, or well\-being needs. * Access to ongoing learning and development opportunities. * Opportunities to support and give back to our communities. * Recognition as one of Greater Toronto's Top Employers and recipient of Insurance Business Canada's 5\-Star Diversity, Equity and Inclusion Award. Make a difference. Be challenged. Be inspired. Be supported. Love what you do. Work for us. A future with Zurich Now is the time to move forward and make a difference. At Zurich, we want you to share your unique perspectives, experiences and ideas so we can grow and drive sustainable change together. As part of a leading global organization, Zurich North America has 2-3 years of experience managing risk and supporting resilience. We are a leading provider of commercial property\-casualty insurance solutions and a wide range of risk management products and services for businesses and individuals. Today, we serve more than 25 industries, from agriculture to technology and insure 90% of the Fortune 500®. Our growth strategy is not limited to our business. As an employer, Zurich strives to provide ongoing career development opportunities and foster an environment where voices are diverse, behaviors are inclusive, actions drive equity, and our people feel a sense of belonging. Be a part of the next evolution of the insurance industry. Join us in building a brighter future for our people, our customers and the communities we serve. Only applicable for Canada: For Zurich Canada's commitment to diversity and accessibility please click here. If you would prefer to not receive future electronic messages from Zurich Insurance Company Ltd's recruitment management system, please email your request to have your job profile deleted from the system by clicking here. Zurich Insurance Company Ltd 100 King St., W., Suite 5500, Toronto, ON, M5X 1C9\. www.zurichcanada.com Work Location: Toronto, Ontario, Canada Availability: Full time
Job Title: Machine Learning Engineer Company: Zurich Insurance Job Category: Machine Learning Roles & Responsibilities: Are you looking for a caring, collaborative, values\-driven workplace with inspiring teammates and leaders? Do you have the ambition and desire to be the best and thrive at the most impactful global insurance provider in the world? Look no further than Zurich Canada. Zurich Canada is expanding its AI Engineering capability and is looking for Machine Learning / AI Engineers to design, develop and operationalize scalable AI and machine learning solutions. What you will do -------------------- * Build/productionize predictive ML/AI: classification, regression, forecasting and clustering. * Build feature pipelines; establish training, validation/testing and bias/fairness testing. * Evaluate models; move experiments to production and optimize inference. * Assess approved A/B, shadow or controlled pilots; monitor data quality, performance/drift and troubleshoot production issues. * Document assumptions, limitations, versions, training\-data references and approvals. * Engineer, evaluate and productionize enterprise GenAI using foundation models, retrieval and agentic patterns. * Build LLM services and RAG pipelines covering ingestion, parsing, cleaning, chunking, embeddings, indexing/retrieval. * Evaluate keyword, semantic\-vector/hybrid search, filtering/reranking; design prompts, structured outputs/context management. * Improve groundedness through retrieval quality, grounding checks, citations, abstention and human review. * Build controlled agentic workflows/tool integrations; evaluate retrieval, answers, safety, agent behaviour/business outcomes. * Monitor quality, groundedness, safety, latency, reliability/cost; apply access\-aware retrieval, sensitive\-data controls and prompt\-injection defences. * Maintain auditable model, prompt, data, index and evaluation records. * Build/operate enterprise\-scale data, feature and engineering foundations for ML/AI. * Develop training and batch/real\-time inference pipelines, reusable feature frameworks and batch/streaming components. * Optimize Spark/distributed processing; build secure data\-platform/AI interfaces and reusable libraries/templates. * Implement ML dataset quality monitoring; support feature management, lineage/reproducibility. * Engineer large\-scale structured/unstructured data; deploy, monitor and troubleshoot production ML data pipelines. * Build/operate platforms, automation and controls across the ML/AI lifecycle. * Design CI/CD for models/AI applications; establish model registration, versioning, lineage/promotion. * Build reproducible training/deployment environments; support staged releases, shadow deployments/rollback. * Monitor health, latency, data quality, model performance/drift; develop retraining/redeployment workflows with validation/approvals. * Manage ML infrastructure/configuration; implement access controls, audit trails/governance evidence and reusable MLOps standards. * Python and SQL skills. * Software engineering fundamentals including Git, APIs, testing and CI/CD. * Understanding of ML concepts and the model\-development lifecycle. * Experience with data processing and analytical workloads. * Experience in cloud\-based development environments. * Understanding of reliable, maintainable, production\-ready solutions. * Databricks, MLflow and Apache Spark/PySpark. * Microsoft Azure or equivalent AWS/Google Cloud technologies. * Azure DevOps or GitHub. * Docker and containerized applications. * REST APIs. * scikit\-learn, PyTorch, TensorFlow or comparable ML/deep\-learning frameworks. * Azure OpenAI or comparable managed AI platforms. * RAG, embeddings, retrieval and LLM evaluation. * Infrastructure as code, Kubernetes and production observability. * Security, privacy, Responsible AI and model governance in a regulated environment. * Work on defined ML/AI engineering tasks with guidance. * Write reliable Python and SQL. * Develop/test components within established architecture and engineering patterns. * Understand core ML and software\-engineering practices. * Participate in code reviews and troubleshooting. * Learn Zurich's AI engineering, security and governance standards. * Independently design/deliver ML/AI components and solutions. * Own development through production implementation. * Make appropriate engineering and technology choices. * Troubleshoot complex data, model and production issues. * Contribute to architecture and engineering standards. * Mentor junior team members. * Work with stakeholders to refine technical requirements. We value diverse perspectives and foster a collaborative environment where employees are empowered to make an impact. We offer a comprehensive rewards package designed to support employee well\-being, growth, and success. * Comprehensive health and wellness benefits. * Minimum four weeks of vacation annually. * Four personal days each year to support personal, cultural, religious, or well\-being needs. * Access to ongoing learning and development opportunities. * Opportunities to support and give back to our communities. * Recognition as one of Greater Toronto's Top Employers and recipient of Insurance Business Canada's 5\-Star Diversity, Equity and Inclusion Award. Make a difference. Be challenged. Be inspired. Be supported. Love what you do. Work for us. Now is the time to move forward and make a difference. At Zurich, we want you to share your unique perspectives, experiences and ideas so we can grow and drive sustainable change together. As part of a leading global organization, Zurich North America has 0 years of experience managing risk and supporting resilience. We are a leading provider of commercial property\-casualty insurance solutions and a wide range of risk management products and services for businesses and individuals. Today, we serve more than 25 industries, from agriculture to technology and insure 90% of the Fortune 500®. Our growth strategy is not limited to our business. As an employer, Zurich strives to provide ongoing career development opportunities and foster an environment where voices are diverse, behaviors are inclusive, actions drive equity, and our people feel a sense of belonging. Be a part of the next evolution of the insurance industry. Join us in building a brighter future for our people, our customers and the communities we serve. Only applicable for Canada: For Zurich Canada's commitment to diversity and accessibility please click here. If you would prefer to not receive future electronic messages from Zurich Insurance Company Ltd's recruitment management system, please email your request to have your job profile deleted from the system by clicking here. Zurich Insurance Company Ltd 100 King St., W., Suite 5500, Toronto, ON, M5X 1C9\. www.zurichcanada.com Work Location: Waterloo, Canada Availability: Full time
Job Title: Senior Machine Learning Engineer Company: ServiceNow Job Category: Machine Learning Roles & Responsibilities: Job Description The Machine Learning Developer designs, builds, ships, and operates applications whose core behavior is model\-driven rather than explicitly authored. The Developer builds the engine behind ServiceNow's optimization products — the algorithms and pipelines that turn sophisticated scheduling and resource\-allocation problems into fast, reliable customer outcomes. The work is evolving — where "AI\-driven" once meant applying ML techniques to optimization problems, it now also means using AI agents as part of the build process itself. This role expects both: someone who can design an efficient algorithm from scratch, and someone who can specify a problem precisely enough to direct an AI agent to implement part of it, then verify the result is correct. The developer owns the correctness, performance, and robustness of what ships, regardless of whether a human or an agent wrote it. What You Get To Do * Build Optimization applications. Design, build and operate applications built around advanced optimization models in production at scale. This includes API design, data ingestion, multiprocessing, observability, advanced algorithm development, performance benchmarking, and automated testing. * Build automated evaluation and test model behaviour. Design and operate the evaluation system that supports development and delivering features with confidence. * Specify precisely and direct AI coding agents. Convert requirements into testable specifications with explicit scope, constraints, and acceptance criteria; decompose work into agent\-sized tasks; and review agent output for correctness and maintainability. Contribute to teams AI\-harness helping shape the way agents are leveraged. * Own quality, safety, and reliability in production. Manage deployments, monitor service availability, implement alerting and respond to customer issues before they even know they have a problem. * Deliver as a forward deployed engineer. Work closely with customers when the work calls for it. Understanding business requirements and product capabilities to help customers get to value faster and use learnings to influence product roadmap. * Collaborate across product, design, and engineering. Partner with product managers, designers, conversation designers, and engineers to define success criteria, align on tradeoffs, and communicate capability and risk clearly. Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third\-party service. Work Location: Toronto, Ontario, Canada Availability: Full time
Job Title: DevOps Engineer (ML Infrastructure) Company: Capgemini Engineering Job Category: Machine Learning Roles & Responsibilities: At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life\-saving robots, our digital and software technology experts think outside the box as they provide unique R\&D and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days are the same. This role is fully remote, anywhere in the Canada We are seeking a highly skilled Senior DevOps Engineer to help build, operate, and evolve large\-scale, business\-critical infrastructure platforms. This role focuses on reliability, scalability, automation, and operational excellence across distributed systems supporting high\-volume production workloads. You will work closely with software engineers, platform teams, and infrastructure specialists to deliver highly available services, improve developer productivity, modernize infrastructure, and drive innovation through automation and AI\-assisted operations. #### Your role * Develop and manage cloud\-native infrastructure supporting large\-scale ML workloads on Kubernetes. * Implement and operate batch scheduling solutions such as Volcano and Kueue to optimize utilization of GPU and compute resources. * Build and maintain CI/CD pipelines for ML services, infrastructure, and platform components. * Manage and optimize Kubernetes environments, including production workloads running on AWS EKS and other cloud platforms. * Lead and support infrastructure modernization and migration initiatives across cloud and platform ecosystems. * Partner with Data Scientists, ML Engineers, and Software Engineers to productionize machine learning solutions. * Implement robust observability, monitoring, and alerting distributed systems and GPU clusters. * Ensure platform reliability, security, scalability, and operational excellence. * Troubleshoot complex distributed systems and performance bottlenecks across infrastructure and ML workloads. #### Your skills and experience * Strong experience with Kubernetes and large\-scale workload orchestration. * Hands\-on experience with Kubernetes batch schedulers such as Volcano / Kueue * Solid understanding of Distributed systems, Containerization technologies, Cloud\-native architectures and Microservices\-based platforms. * Experience managing workloads on Kubernetes platforms such as AWS EKS. * Proven track record delivering and supporting infrastructure migration projects. * Strong programming skills in Python or Golang * Experience with Infrastructure\-as\-Code and deployment tools including Terraform / Helm. * Experience designing and maintaining CI/CD pipelines using GitHub Actions, Jenkins, GitLab CI/CD, or Azure DevOps and * Strong Linux systems administration and troubleshooting skills * Experience building observability solutions using: Prometheus, Grafana and * Understanding of ML lifecycle management, model deployment, and production operations. The base compensation range for this role in the posted location is: $72,056\- $138,940/year Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law. Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55\-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end\-to\-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem. Work Location: Toronto, ON, Canada Availability: Full time
Job Title: Staff Research Scientist (AI for Self-Driving Labs, 2-year Term) Company: University of Toronto Job Category: Machine Learning Roles & Responsibilities: Department: Acceleration Consortium The Acceleration Consortium (AC), based at the University of Toronto (U of T), is a global community of academia, industry, and government working to accelerate the discovery and development of advanced materials and molecules. The AC develops self\-driving laboratories (SDLs), autonomous research platforms that integrate artificial intelligence, robotics, automation, and advanced computing to dramatically reduce the time and cost of scientific discovery. AC Staff Research Scientists are highly skilled, experienced, and independent researchers that develop the AI and automation technologies required to build robust and scalable self\-driving labs, manage these SDLs, and design and implement collaborative research programs that leverage the SDLs to accelerate discovery. Staff Scientists will advance SDL technologies and apply them to challenges in areas such as clean energy, sustainability, healthcare, and advanced manufacturing. The Acceleration Consortium (AC) promotes inclusive research environment and supports the EDI priorities of the unit. The Acceleration Consortium received a $200M Canadian First Research Excellence Grant for seven years to develop self\-driving labs for chemistry and materials, the largest ever grant to a Canadian University. This grant will provide the Acceleration Consortium with seven years of funding to execute its vision. The AC operates and continuously develops seven SDLs as core facilities: This posted position is for a role within SDL0: AI \& Automation. Staff Research Scientists will work with a diverse team of leading experts at U of T, including Faculty and Staff Scientists in and associated with SDL0 such as: Alán Aspuru\-Guzik, Anatole von Lilienfeld, Kourosh Darvish, Florian Shkurti, Chris Sutton, Willi Gottstein, and more. Moreover, the Staff Scientists will work collectively, sharing knowledge among each other (spanning all AC labs), local and global AC faculty, and the many trainees that work in these labs. This role will report to the Academic Director and Executive Director of the Acceleration Consortium. The components and duties of the work can include: * SDL and Automation Development Working with the AC community, develop research programs that leverage the AC’s SDLs and support the research objectives of AC faculty and industry partners. Using SDLs to synthesize and characterize large quantities of candidate molecules, calibrating theoretical models with experimental data, predicting promising candidates with computational tools and machine learning algorithms, and elucidating structure\-property relationships of emerging molecules, polymers, solid\-state materials, formulations, etc. * Implementing research and development projects of AC’s industry partners when implemented in AC labs * Developing plans supporting research collaborations and estimating financial resources required for programs and/or projects. * Working with Product Managers to ensure research outcomes meet partner requirements. * Promoting AC’s research capacity, including delivering presentations at conferences. * Collaboration in preparing and submitting research proposals to granting agencies and progress reporting. * Preparing manuscripts for submission to peer review publications/journals and stewarding them through the process. * Supporting consulting services related to the application of SDLs for materials discovery for the AC’s partners. * Support research\-focused events such as Annual Symposium. 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
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: Toronto, Canada Availability: Full time
Job Title: 2027 Accelerated Development Program - BrainBox AI Company: Trane Technologies Job Category: Machine Learning Roles & Responsibilities: Be a part of our mission! As a world leader in creating comfortable, sustainable, and efficient climate solutions for buildings, homes and transportation, it's our responsibility to put the planet first. For us at Trane Technologies, and through our businesses including Trane® and Thermo King, sustainability is not just how we do business—it is our business. Do you dare to look at the world's challenges and see impactful possibilities? Do you want to contribute to making a better future? If the answer is yes, we invite you to consider joining us in boldly challenging what's possible for a sustainable world. Ce Que Vous Ferez Programme de développement accéléré – IA et analytique Canada Les programmes de développement accéléré (ADP) de Trane Technologies offrent aux personnes récemment diplômées de l’université des affectations stimulantes, une formation en leadership et une exposition précieuse aux hauts dirigeants de notre entreprise. Grâce à des rotations et à des expériences dans plusieurs emplacements géographiques et secteurs d’activité, vous pourrez développer des compétences diversifiées et une base solide pour une carrière réussie et enrichissante chez Trane Technologies. Ces affectations sont choisies stratégiquement afin d’assurer votre apprentissage continu et votre développement personnel. * Baccalauréat en analytique ou dans un domaine connexe, comme l’informatique, le génie logiciel, la gestion des systèmes d’information, les statistiques, les mathématiques, l’analytique, la science des données ou un domaine similaire, avec une moyenne cumulative générale de 3,0 ou plus, complété avant la date d’entrée en fonction. * Fort intérêt pour une carrière comme ingénieure ou ingénieur en IA, ingénieure ou ingénieur de données, analyste de données ou scientifique des données. * Compétences démontrées en leadership: au moins deux exemples, comme dirigeante ou dirigeant d’un club scolaire, capitaine d’une équipe sportive, conseillère ou conseiller en résidence, etc., ou un leadership exceptionnel dans des projets de travail. * Expérience de travail: au moins un stage lié au diplôme ou six mois d’expérience de travail connexe en IA * Voit les problèmes comme des occasions et peut s’adapter rapidement à des circonstances d’affaires nouvelles ou changeantes. * Cherche avec empressement et de manière proactive à acquérir de nouvelles informations, compétences et expériences, en tirant parti des occasions d’apprentissage. * Travaille efficacement avec les autres pour coordonner les efforts et produire des résultats dans un environnement de travail positif. * Motivation à mettre à profit les principaux apprentissages et expériences pour faire progresser votre propre carrière tout en contribuant à la croissance de Trane Technologies. * Maîtrise des outils analytiques tels que: Python, R, SQL, Tableau ou d’autres logiciels de visualisation, ainsi que des outils infonuagiques comme BigQuery, Redshift. * Capacité à comprendre les problèmes présentés par l’entreprise et à recommander la meilleure approche pour répondre aux besoins des clients internes. * Demeurer flexible sur le plan géographique pendant et après la fin du programme. * Être citoyenne ou citoyen canadien ou avoir le droit légal de travailler au Canada sans nécessiter de parrainage maintenant ou à l’avenir. Be a part of our mission! As a world leader in creating comfortable, sustainable, and efficient environments, it’s our responsibility to put the planet first. For us at Trane Technologies, sustainability is not just how we do business—it is our business. Do you dare to look at the world's challenges and see impactful possibilities? Do you want to contribute to making a better future? If the answer is yes, we invite you to consider joining us in boldly challenging what’s possible for a sustainable world. What you will do: Our Accelerated Development Program in AI \& Analytics in Canada consists of these rotations: * Intro to AI \& Analytics (12 months, focused on data, technology, and/or machine learning) in the BrainBox AI Trane Technologies AI Lab in Montreal, Quebec * Applied AI \& Analytics (9 months, focused on applying AI to business opportunities) in Trane Technologies, Trane, or Thermo King, in Davidson, NC, or Minneapolis, MN * AI Solutions (9 months, focused on building and deploying AI solutions for customers) in the BrainBox AI Trane Technologies AI Lab in Montreal, Quebec ADP participants will develop a solid foundation in data exploration, analytics, data science, machine learning, artificial intelligence, AI solutions engineering, and AI deployment over the course of the 2\.5 year program. They will gain skills in our technology stack, pipeline development, and the creation of AI solutions to help our businesses and customers optimize efficiency and performance. Assignments are strategically chosen to ensure continuous learning and personal development in a range of businesses. The program can include up to three physical moves. Relocation assistance is provided for new work locations where the distance is at least 50 miles. Responsibilities Function specific responsibilities will vary based on the assignment. A successful candidate for the Accelerated Development Program will exhibit the following: * BS/BA in Analytics related field such as Computer Science, Software Engineering, Management of Information Systems, Statistics, Mathematics, Analytics, Data Science or similar with a cumulative overall GPA at or above 3\.0, completed prior to start date. * Strong interest in a career as an AI engineer, data engineer, data analyst, or data scientist. * Demonstrated leadership skills: minimum of two examples such as school club officer, sports team captain, resident advisor, etc. or exceptional leadership of work projects. * Work Experience: Minimum of one degree\-related internship or six months of related AI\-based work experience * Views problems as opportunities and can adapt quickly to new or changing business circumstances. * Eagerly and proactively seek new information, skills, and experiences, capitalizing on learning opportunities. * Works effectively with others to coordinate efforts and produce results in a positive work environment. * Motivated to leverage key learnings and experiences to grow your own career while contributing to the growth of Trane Technologies. * Proficient in utilizing analytical tools such as : Python, R, SQL, Tableau, or other visualization software, cloud\-based tools like BigQuery, Redshift. * Ability to understand problems presented by the business, and to recommend the best approach to address the needs of internal customers. * Remain geographically flexible both during and after completion of the program. * Canadian citizen or have the legal right to work in Canada without requiring sponsorship now or in the future. Work Location: Montreal, Quebec, 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 * Extended health and dental coverage options, along with life insurance and disability benefits * Mental health benefits * Family building benefits * Child care and pet benefits * Access to a Lyft funded Health Care Savings Account * RRSP plan with company match to help save for your future * In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service * Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top\-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible. * Subsidized commuter benefits and Lyft ride credits 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, Canada Availability: Full time
Job Title: Principal Software Development Engineer Company: Workday Job Category: Machine Learning Roles & Responsibilities: 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. Agent Factory is where Workday’s next chapter gets built. We’re forming small, senior, cross\-functional AI teams that bring together product leaders, machine learning engineers, and full\-stack builders to create intelligent agents used by millions of people every day. This is production\-grade AI—deeply embedded into Workday’s platform—not research experiments or maintenance work. Teams own problems end to end, collaborate tightly across disciplines, and use the right tools to solve real customer challenges at global scale. You’ll work at the intersection of AI, platform architecture, and human workflows, with the autonomy to shape how agents reason, act, and scale responsibly. High trust, high expectations, and real impact. Engineering, but brighter. About the Role As a Principal Full Stack Software Engineer in Agent Factory, you’ll help build the user\-facing and platform experiences that bring Workday’s AI agents to life. Working within a small, cross\-functional pod, you’ll design and ship full stack solutions—from intuitive front\-end experiences to resilient backend services that integrate AI\-driven capabilities deeply into HR and Finance workflows. This role is about turning powerful technology into products people actually use: scalable, reliable systems that simplify complex business processes for customers around the world. You’ll collaborate closely with machine learning engineers, product managers, and platform teams, owning features end to end and seeing your work run in production. If you enjoy building real products, solving meaningful problems, and working with people who care about quality and craft, you’ll feel right at home here. Your responsibilities: 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! Work Location: Vancouver, BC, Canada Availability: Full time
