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Lead Solution Architect for a Databricks practice, owning end-to-end data platform architecture, leading presales with C-level stakeholders, and driving large-scale cloud migration programs across APAC using Databricks, Spark, and Delta Lake on Azure/AWS/GCP.
DevOps AI role focused on designing and maintaining cloud infrastructures, CI/CD pipelines, and MLOps environments for AI solution deployment in production, working within an agile team alongside AI developers and data scientists.
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.
Design, build, and operate scalable data infrastructure and MLOps platforms for Doodle's B2B SaaS scheduling product, using Python, SQL, cloud infrastructure, containers, and IaC.
Build and deploy production-grade ML and GenAI systems for insurance, banking, and wealth management using Python, MLOps, and cloud-native tools.
Build ML infrastructure—training pipelines, model registries, and deployment systems—for XYZ Reality's Construction Intelligence platform, using Python, PyTorch, Docker, and Kubernetes to take AI models from research into production on wearable AR devices.
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.
Develop and deploy GenAI solutions (LLMs, RAG, agents, copilots) in Python, integrating AI models into internal systems via APIs while ensuring production readiness and AI Act compliance.
Senior Software Engineer building scalable AI-powered backend and front-end systems that extract insights from unstructured engineering documents (CAD/BIM, technical reports). Core stack: Python (FastAPI/Flask/Django), React/TypeScript, LLM/RAG integration, vector databases, and multi-cloud deployment.
Senior Data Engineer placed at Enexis to build data infrastructure, pipelines, and CI/CD solutions using sensor data for grid-load and risk insights, working with Python, SQL, Docker, Git, AWS, Airflow, and MLflow.
Builds and scales the ML compute platform for autonomous driving, focusing on Kubernetes-based orchestration, distributed training, and resource governance using tools like Argo Workflows and Ray.
Empowering people. Unlocking innovation. With 1,000+ professionals and over a decade of experience, we’ve built an environment where talent is trusted, supported and continuously challenged to grow. Aumente sus…
Lead the industrialization and productionization of data pipelines, ML models (including LLMs/AI Agents), and AI solutions in a financial sector client environment, coordinating across Data Science, Engineering, Architecture and Ops teams using Python, PySpark, AWS, Docker, Kubernetes and MLflow.
From Q-tech, we are collaborating with a large European technology company , part of a leading international retail and distribution group, that is looking for a Data Engineer to join a highly innovative squad within…
About the company Are you tired of missing important moments in your weekly game because no one recorded you? Say goodbye to FOMO and hello to PUSHIT! PUSHIT allows you to easily catch up on all the highlights you did…
The Senior Data Science Engineer will own the full lifecycle of risk detection systems, building and deploying LLM and classical ML models within a SaaS platform. The role requires a blend of data engineering, MLOps, and applied machine learning to develop scalable pipelines and production-ready AI solutions.
Build and maintain full-stack marketplace features and ML Ops infrastructure to match renters with homes, using Ruby/JavaScript/Go/Python and tools like Vertex AI and Chalk.
Senior ML Engineer designing scalable AI platforms, defining governance frameworks, and leading cross-team ML strategy to deploy safe, high-impact models at Creai, a data-driven AI startup.
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.
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