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Design and maintain scalable cloud-based data platforms using Azure and AWS, enabling analytics and ML workflows for a large Canadian insurer.
Design and maintain scalable cloud data platforms using Azure and AWS, focusing on ML lifecycle support, DevOps, and cross-functional collaboration in a hybrid Toronto/London role.
Secure AWS cloud environments and AI-driven pipelines for a healthcare supply-chain platform, using Wiz CNAPP, Code-to-Cloud tracing, and LLM guardrails to prevent vulnerabilities and adversarial attacks.
Job Description Build & optimize a high performance data platforms that powering analytics, dashboards , and AI models Pioneer team to freeing Data Scientists & Analysts team from manual engineering Salary up…
Senior DevOps Engineer (AWS/IA) Se anima a todos los posibles solicitantes a que se desplacen y lean la descripción completa del puesto antes de presentar su candidatura. - Remoto We are still looking for the very Top…
Build and maintain AWS-based Kubernetes infrastructure and CI/CD pipelines for a mental-health platform, using Terraform, Helm, and Python to automate deployments and enforce security policies.
Build and scale the data platform that ingests, processes, and serves telemetry and sensor data from a fleet of humanoid robots, using Spark, Kafka, OpenTelemetry, and cloud tools.
Desde ISPROX buscamos para uno de nuestros clientes del sector tecnológico un/a Senior DevOps Engineer especializado/a en AWS. Te incorporarás a un equipo de Professional Services, trabajando de forma cercana con el…
1 in 4 people in the US have a treatable mental health condition, but most providers don't accept insurance, making therapy too expensive for most people. Headway’s mission is to fix this by building a new mental…
About Calpion is an 18-year-old Dallas-headquartered technology firm that offers customers artificial intelligence solutions by building custom deep learning and machine learning algorithms, custom enterprise…
Build and maintain cloud-based data platforms on AWS, designing batch/streaming pipelines with PySpark, Python, and SQL to power analytics and ML workloads.
Lead data-science engineering projects for public and private-sector clients, building scalable ML pipelines and recommender systems in Python and cloud tools like AWS SageMaker.
Designs, builds, and optimizes scalable AWS data pipelines (EMR, SageMaker) while collaborating with data science teams to enable ML workflows.
Build and maintain the internal backbone for an AI startup focused on policing, connecting APIs, data pipelines, cloud infrastructure, and ML models using Node, NestJS, Typescript, and AWS services.
Build AI-driven healthcare applications end-to-end using Python/TypeScript, agent frameworks, and vector databases, deploying on cloud platforms while owning the full stack from design to production.
Architect and lead Faire’s ML platform, setting standards for MLOps, feature management, and scalable ML workflows using Databricks, Spark, and MLflow to empower data scientists and retailers.
Build and maintain scalable data pipelines for a machine-learning team at a major bank, using Python, SQL, and cloud tools like AWS, Snowflake, and dbt.
Designs and implements cloud-native AI/ML solutions on AWS, focusing on Bedrock, SageMaker, and Lambda with Python and Golang.
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