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Machine Learning Engineer at Manulife designing, building, and operating ML/AI platforms and pipelines from experimentation to production at scale, using Python, CI/CD tools, Docker/Kubernetes, Terraform, and Azure cloud services.
The Principal AI Engineer will lead the design and implementation of agentic AI systems and data platforms within a financial services environment. The role involves building RAG solutions, scalable data pipelines, and AI observability frameworks using technologies like Python, Spark, and Databricks.
Senior API developer designing and building REST API platforms (Apigee), web applications (React, Node.js, Next.js), and AI/ML integrations (LangChain, RAG, XGBoost) on-site in Toronto.
Are you passionate about backend engineering, API architecture, and the future of AI-native software delivery? At Qaracter, we are looking for an AI-Native Backend/API Technical Lead to join strategic technology…
Leads end-to-end design and deployment of production-grade AI/ML and GenAI solutions, focusing on RAG platforms, agentic systems, and secure enterprise integrations using Python, AWS/Azure, and MLOps practices.
Build and deploy end-to-end GenAI/LLM applications (RAG, agentic workflows, evaluation pipelines) using Python, cloud platforms, Docker, and vector databases for a finance consulting firm in Pune.
The Data Scientist will design and implement scalable AI and Generative AI solutions to improve business efficiency and customer experience. The role involves building production-grade applications using Python, SQL, LLMs, RAG, and agentic AI frameworks.
Staff ML Engineer architecting and deploying production GenAI systems (LLM-powered features, RAG workflows, agentic apps) on a team building AI-powered identity/security infrastructure, primarily using Python.
Design and deploy production-scale GenAI systems, including RAG pipelines, agent frameworks, and evaluation workflows, to power secure AI-powered identity features.
Build and deploy production-grade ML and GenAI systems for insurance, banking, and wealth management using Python, MLOps, and cloud-native tools.
Build and operate cloud-native AI/ML platform services at BMO as a new graduate, focusing on Infrastructure as Code, CI/CD pipelines, and scaling AI infrastructure using Azure/AWS/GCP.
Onsite Software Developer building REST APIs and web applications with React, TypeScript, Node.js, and Next.js, plus AI/ML integrations (Agentic AI, RAG, LLMs) for a government/public sector client in Toronto or Peterborough.
Designs and leads secure, scalable Gen AI applications across frontend, backend, cloud, and agentic AI layers, setting architecture direction, mentoring teams, and ensuring production-ready solutions using RAG, LLMOps, and multi-cloud platforms.
GFT es una compañía pionera en transformación digital. Si cree que es el candidato ideal para la siguiente oportunidad, envíe su solicitud después de leer la descripción completa. Diseñamos soluciones de negocio…
Additional Location(s): N/A Diversity - Innovation - Caring - Global Collaboration - Winning Spirit - High Performance At Boston Scientific, we’ll give you the opportunity to harness all that’s within you by working in…
Databricks-focused Data Engineer at a digital product consultancy, designing and building production data pipelines, Lakehouse architectures, and AI/ML foundations on Databricks for client engagements.
Lead the design, build, and deployment of production data and AI solutions using Palantir Foundry and AIP, working directly with enterprise clients in a consulting capacity.
The Data DevOps Engineer will develop, deploy, and maintain data pipelines and machine learning workflows within a multi-cloud environment. The role involves collaborating with data scientists to optimize analytics platforms using tools like Python, Kubernetes, and various Big Data technologies.
Designs, builds, and deploys enterprise-scale AI solutions including GenAI agents, RAG pipelines, and LLM-driven workflows using Azure AI services, while ensuring scalability, security, and Responsible AI compliance.
Senior engineer designs, builds, and secures Azure cloud infrastructure for data and analytics workloads using Terraform and Azure DevOps, deploying services like Databricks and Data Factory in a hybrid Canberra role.
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