Job Title: Senior Data Engineer Company: Equifax Job Category: Machine Learning Roles & Responsibilities: Manage Preferences Equifax is where you can power your possible. If you want to achieve your true potential, chart new paths, develop new skills, collaborate with bright minds, and make a meaningful impact, we want to hear from you. Synopsis of the role Equifax is seeking a Senior Data Engineer to join our world\-class Entity Resolution/Keying \& Linking team within India Data \& Analytics. The ideal candidate is an analytical engineer who bridges the gap between software development and data science—possessing the programming skills to scrape, merge, and manage diverse data streams, alongside the statistical mindset to extract meaningful insights. You will combine technical execution with creative problem\-solving to build reliable data prototypes and uncover patterns within complex data. If you have a solid foundation in mathematics or statistics and a passion for data mining and machine learning, we want to hear from you. * Pipeline Engineering: Build and manage reliable data pipelines to aggregate, ingest, and process data from diverse source systems. * Data Integration \& Quality: Integrate, cleanse, and structure large datasets for analytical consumption and client solutions, implementing automated checks to troubleshoot data anomalies. * Model Support: Apply an understanding of data characteristics to develop tracking processes that support data quality and entity resolution models. * Cloud \& Infrastructure: Leverage and implement Google Cloud Platform (GCP) technologies, keeping up with cloud advancements to propose optimization improvements. * Data Governance: Implement data management, security, and maintenance best practices directly into pipeline workflows. * Global Teamwork: Collaborate actively with regional and global Equifax teams to share insights, standardize workflows, and adopt best practices. At Equifax, we believe knowledge drives progress. As a global data, analytics and technology company, we play an essential role in the global economy by helping employers, employees, financial institutions and government agencies make critical decisions with greater confidence. We work to help create seamless and positive experiences during life’s pivotal moments: applying for jobs or a mortgage, financing an education or buying a car. Our impact is real and to accomplish our goals we focus on nurturing our people for career advancement and their learning and development, supporting our next generation of leaders, maintaining an inclusive and diverse work environment, and regularly engaging and recognizing our employees. Regardless of location or role, the individual and collective work of our employees makes a difference and we are looking for talented team players to join us as we help people live their financial best. Work Location: Karnataka, India Availability: Full time

Job Title: Senior Data Scientist - AI/ML Company: ACROSSTEK™ Job Category: Machine Learning Roles & Responsibilities: We are looking for a Senior Data Scientist with a strong foundation in Machine Learning, Algorithms, Statistical Modeling, and AI\-native development to contribute to advanced AI initiatives and real\-time analytics platforms. This is a hands\-on, technically deep role for professionals passionate about building scalable and intelligent ML solutions. Key Responsibilities \- Develop solutions for predictive modeling, anomaly detection, forecasting, and automated alerting. \- Develop POCs and take ML solutions from experimentation to production. \- Leverage AI coding tools such as Claude, Cursor, or GitHub Copilot for development, debugging, prototyping, and solution design. Work Location: Greater Bengaluru Area Availability: Full time

Job Title: Staff Data Scientist Company: Qualcomm Job Category: Machine Learning Roles & Responsibilities: General Summary The Staff Data Scientist / Full Stack Developer is a senior, hands on individual contributor responsible for designing, building, and operationalizing traditional machine learning models, agentic AI systems, and Databricks native data applications that drive real business outcomes. This role operates at the intersection of data science, ML engineering, and full stack data application development, with a strong focus on production grade solutions. This position requires deep expertise with AI assisted development of classic ML techniques, agent based AI workflows, and Databricks application development, along with strong ownership of end to end delivery—from data preparation and modeling to deployment, monitoring, and user facing experiences. Key Responsibilities * Design, develop, and deploy traditional machine learning models, including regression, classification, clustering, time series forecasting, and anomaly detection. * Perform feature engineering, model selection, training, validation, and performance tuning on large scale enterprise datasets. * Apply sound statistical and ML best practices to ensure model robustness, explainability, and business relevance. * Design and implement agentic AI workflows, where autonomous or semi autonomous agents orchestrate data access, ML inference, decision logic, and actions. * Build multi step agent pipelines that combine rules, ML models, and reasoning components to solve complex business problems. * Integrate agentic systems with enterprise data, ML models, and applications to enable intelligent automation and decision support. Databricks Application Development * Design and develop Databricks native applications, including notebook based apps, interactive dashboards, and parameterized data/ML workflows. * Build data and ML services/APIs leveraging Databricks, Python, and Lakehouse capabilities. * Partner with analytics, BI, and application teams to embed ML insights, predictions, and agent outputs directly into Databricks apps and business workflows. * Ensure Databricks apps meet performance, security, governance, and usability standards. * Operationalize ML models and agentic workflows into production pipelines, ensuring scalability, reliability, and monitoring. * Collaborate with data engineering teams to leverage curated Lakehouse data, feature stores, and governed datasets. * Implement model monitoring, drift detection, and retraining strategies to maintain long term model effectiveness. * Develop end to end solutions that span data ingestion, modeling, ML inference, agent execution, and user facing applications. * Translate business and analytical requirements into scalable, maintainable ML powered data products. * Enable downstream consumption through Databricks apps, dashboards, APIs, and integrated enterprise applications. Production Support \& Operational Excellence * Own production ML models, agentic systems, and Databricks applications, including monitoring, troubleshooting, and root cause analysis. * Implement logging, alerting, and observability for models, agents, and applications. * Drive continuous improvements in model accuracy, system reliability, and user experience. Technical Leadership \& Influence * Familiarity with Lakehouse architectures, feature stores, and ML lifecycle management. * Experience with MLOps practices, CI/CD, model monitoring, and retraining pipelines. * Exposure to cloud platforms (e.g., AWS) and scalable ML infrastructure. * Experience embedding ML and agent outputs into enterprise applications or analytics platforms. * Knowledge of data governance, access controls, and secure ML deployment. 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: Greater Hyderabad Area Availability: Full time

Job Title: Applied Machine Learning Scientist Company: Jump! Recruiters Job Category: Machine Learning Roles & Responsibilities: Our client, 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. They are currently looking at adding an Applied Machine Learning Scientist, who 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. 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. Work Location: Greater Toronto Area, 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 AI/ML Engineer Company: RBC Job Category: Machine Learning Roles & Responsibilities: Job Description What is the opportunity? Are you a creative, results\-driven professional passionate about delivering high\-performing AI solutions? Join our collaborative and innovative team within Global Payments Technology, where your ideas and contributions are valued. Global Payments Technology is part of RBC’s Technology and Operations division, collaborating with partners across the company to deliver innovative IT solutions. Our clients span various departments, including Risk, Finance, HR, and more. We lead the development of digital tools and platforms to enhance collaboration and are known for our culture of innovation, inclusivity, and collaboration. This role is part of the Global Payments Technology team, focusing on building AI agents powered by AI and Large Language Models (LLMs) to deliver value within the Global Payments domain. What will you do? * Develop and train AI models, including LLMs, to create intelligent agents for various use cases. * Collaborate with the team to design and implement AI solutions for anomaly detection and payments process automation. * Preprocess and analyze data to ensure model accuracy and performance. * Deploy and monitor AI models in production environments. * Contribute to research and development of new AI techniques and technologies. * A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock where applicable * Leaders who support your development through coaching and managing opportunities * Ability to make a difference and lasting impact * Work in a dynamic, collaborative, progressive, and high\-performing team * Flexible work/life balance options * Opportunities to do challenging work * Opportunities to take on progressively greater accountabilities * Access to a variety of job opportunities across business Job Skills Big Data Management, Data Mining, Data Science, Deep Learning, Machine Learning (ML), Predictive Analytics, Programming Languages Note : Applications will be accepted until 11:59 PM on the day prior to the application deadline date above* Our Employment Opportunities At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC. We believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all. Work Location: Toronto, Ontario, Canada Availability: Full time

Job Title: Staff Data Engineer Company: RBC Job Category: Machine Learning Roles & Responsibilities: Job Description RBC Wealth Management (WM) Data \& AI is responsible for driving data driven decision making end\-to\-end across our global businesses. We're modernizing our data architecture, building out BI and analytics capabilities, and developing cutting\-edge AI/ML solutions—from traditional machine learning to Generative AI—to support our Global Executive Leadership as well as our Digital and Global Investment teams. * Architect, establish, maintain, and evolve the data foundation and analytical environments that support BI/analytics workloads and downstream AI/ML consumers with high performance and reliability * Design, build, and maintain scalable, production\-grade data pipelines that ingest, transform, and serve both structured and unstructured data across WM LoBs * Design data models and schemas that serve multiple consumer types—BI dashboards, reporting, and downstream ML pipelines—balancing performance, flexibility, and reusability * Build and maintain APIs and integrations that expose data to downstream consumers, including AI/ML systems and business workflows * Define clean data contracts and interfaces with downstream AI/ML and BI teams—schemas, SLAs, and freshness guarantees—to ensure reliable handoffs * Implement monitoring, logging, and observability for data pipelines to ensure reliability, performance, and compliance * Optimize pipeline and storage performance and cost (e.g., query tuning, partitioning, compute/storage cost management) across Dev, UAT, and Production environments * Create, maintain, and develop data assets across Dev, UAT, and Production environments, ensuring consistency * Identify, source, stage, and model improvements to partially/completely automate the most common, repeatable and tedious manual data preparation and integration tasks, and optimize data delivery for greater scalability, as part of the end\-to\-end data lifecycle * Implement data quality frameworks, automated testing, and monitoring to ensure data integrity and trust across all downstream consumers * Support data cataloging and metadata management practices to ensure data assets are discoverable, well\-documented, and governed * Support DevOps and DataOps best practices, including CI/CD, infrastructure\-as\-code, and automated testing across data pipelines * Use version control systems (e.g., GitHub) and data/schema comparison tooling to manage code and data changes safely across environments * A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock where applicable * Leaders who support your development through coaching and managing opportunities * Ability to make a difference and lasting impact * Work in a dynamic, collaborative, progressive, and high\-performing team * Flexible work/life balance options * Opportunities to do challenging work * Opportunities to take on progressively greater accountabilities * Access to a variety of job opportunities across business Big Data Management, Cloud Computing, Database Development, Data Mining, Data Warehousing (DW), ETL Processing, Quality Management, Requirements Analysis, Waterfall ModelAdditional Job Details WEALTH MANAGEMENTJob Type: At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC. We believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all. Work Location: Toronto, ON, Canada Availability: Full time

Job Title: AI Engineer Company: FGF Brands Job Category: Machine Learning Roles & Responsibilities: AI Engineer (Speech and Audio Systems) We’re a Naan Traditional Company… Job Summary: We are seeking a motivated, detail\-oriented AI Engineer to join our growing Audio Intelligence team. In this role, you will help build, refine, and deploy machine learning models that understand human speech and sound. You will bridge the gap between creative audio engineering and deep learning by processing raw audio datasets, evaluating model performance, and helping us build the next generation of voice\-activated technology. Responsibilities: * Data Curation \& Preprocessing: Clean, segment, and format audio datasets for model training (handling noise reduction, volume normalization, and formatting). * Audio Analysis \& Visual Inspection: Use advanced spectral editing software to inspect, clean, and isolate specific sound events or speech anomalies in our training data. * Model Training Support: Assist in fine\-tuning state\-of\-the\-art automatic speech recognition (ASR) and audio classification models. * Evaluation \& Benchmarking: Run validation tests on trained models, track performance metrics (like Word Error Rate), and document failures to help guide future improvements. * Collaboration: Work closely with senior AI scientists and data engineering teams to maintain high\-quality data pipelines. Disclaimer: The above describes the general responsibilities, required knowledge and skills. Please keep in mind that other duties may be added or this description may be amended at any time. Work Location: Greater Toronto Area, Canada Availability: Full time

Job Title: Machine Learning Intern - Summer 2027 Company: BNP Paribas Job Category: Machine Learning Roles & Responsibilities: Join one of Montreal's Top Employers in 2026\. We are a leading international banking institution fully committed to building a more sustainable future. As an intern, you will benefit from a 4 months program that aims to give you the tools to develop yourself and discover your potential through customized trainings, networking sessions and transversal projects. During the four\-month internship, you will contribute to an applied research project aligned with the Lab’s priorities. These projects explore advanced AI capabilities for our solutions and are designed with the ambition of producing work suitable for a publication at a leading AI conference. Potential topics include agentic AI, AI evaluation, GenAI model specialization, or retrieval\-augmented generation (RAG). BNP Paribas is committed to fostering a work environment where all employees can feel heard, valued, safe and supported, and can be their authentic selves. BNP Paribas, the leading bank in the European Union and a major global financial institution, operates in 63 countries and has nearly 178,000 employees. Its mission is to foster a responsible, sustainable economy by financing and advising clients to the highest ethical standards while addressing environmental, regional development, and social inclusion concerns. With over 1,700 employees in Montreal and Toronto, BNP Paribas in Canada strives to develop long\-term relationships with its clients by supporting their business strategies and meeting their financing and investment needs, both locally and abroad. * BNP Paribas is committed to accessibility and inclusion. During the recruitment process, accommodation needs are available at all times for candidates. You will have the chance to make a request for an accommodation during your application. * You must be legally eligible to work in the Greater Montreal area and, if applicable, hold a valid work or study permit. Physical presence in BNP Paribas’ office(s) is an essential function of this position; * If you are applying and accepted to a position which requires working in/for the U.S. securities industry, you will be required to provide your fingerprints and undergo additional background checks by the FBI. BNP Paribas Securities Corporation is required to maintain a supervisory program over the conduct of its Associated Persons; some of your personal data will be transmitted to the United States of America and made available to US regulators. Please reach out to BNPP for additional information; or you can also find an overview here: 3110\. Supervision FINRA.org Work Location: Montreal, Canada Availability: Full time