Docker

containerization, devops, virtualization
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There was a time when deploying applications felt like a dark art, a chaotic ritual of dependency hell and “it works on my machine” laments. Then came Docker, promising to encapsulate applications and their dependencies into neat, portable containers. Quite clever, really, though one does wonder if we simply traded one set of configuration headaches for another. It's essentially lightweight virtualization, a lovechild of chroot and control groups, allowing developers to package their code and run it consistently across different environments.

The reality? It mostly delivers. While not a silver bullet – Kubernetes quickly became the default orchestration layer, adding its own complexity – Docker remains ubiquitous. Alternatives like Podman exist, offering rootless containers and a slightly different approach, but Docker still dominates the landscape. Pretty much every cloud provider embraces it, and if you're not containerizing your applications in 2024, you're probably doing it wrong…or at least making life significantly harder for your operations team.

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machine learning engineer

Senior Machine Learning Engineer - (Vendor Data) @ delivery-hero-se

DE | 2025-12-28
Delivery Hero’s Senior Machine Learning Engineer for Vendor Data promises end‑to‑end ML at scale across 70+ markets, designing and operating production systems that balance performance with cost.... read more »
AI/ML, Data Science, Cloud Computing, Data Management, MLOps, DataOps, TensorFlow, PyTorch, AWS, GCP, Azure, Docker, Kubernetes, CI/CD, Airflow, Grafana
machine learning engineer

Machine Learning Engineer – Generalist @ national-basketball-association

US | 2025-12-24 | USD 210000 - 300000 / year
An NBA machine learning software engineer on the Automated Officiating team, the role centers on real-time, multi-modal perception for in-game officiating with a 0-to-1 product scope. Expect... read more »
AI/ML, Data Collection, Data Analytics, R, KPI, Computer Science, Docker, Kubernetes, Python, PyTorch, TensorFlow, C++, Management
promoted

O'Reilly: Building AI Agents with Model Context Protocol (MCP)

Design and implement composable agent architectures using MCP. Understand the MCP architecture and how it enables AI applications to access external context. Build MCP servers that expose tools, resources, and prompts to LLMs.

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machine learning engineer

Machine Learning Engineer @ rea-group

AU | 2025-12-24
REA Group promises a hands-on ML engineering role within a top-tier property brand, building scalable multi-modal AI across web and app platforms. The tech stack reads like a tour of modern ML... read more »
AI/ML, GenAI, LLM, API, Cloud Computing, AWS, GCP, Amazon SageMaker, Docker, IaC, Python, DataViz, Analytics, Data Science, SQL, PyTorch, Keras, RDBMS, MySQL, PostgreSQL, BigQuery, NoSQL, Redis, DynamoDB, ELK, Amazon EC2, S3, Terraform, CloudFormation