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Best 20+ Tools for Machine Learning Engineers in 2025

The Machine Learning Engineer designs and implements machine learning systems and algorithms. They work with data scientists, build ML pipelines, deploy models to production, and optimize performance while ensuring scalability and reliability of AI-powered applications.

39 active tools
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LoginRadius

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LoginRadius is a tool that handles user identity and login management for your digital products. When someone visits your website or app, LoginRadius manages their registration, login, and account security. It offers multiple ways for users to sign in, including traditional passwords, social media accounts like Google or Facebook, or passwordless options like magic links.

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Magic

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Magic is a software development kit that helps developers add secure login systems to their applications. When a user wants to log in, they receive a one-time code via email or SMS instead of typing a password. This makes the login process faster and more secure.

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SlateDB

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SlateDB is an embedded storage engine that uses a log-structured merge-tree design and writes everything to cloud object storage. You include it as a library in your Rust applications, and it handles data storage through services like S3 or Google Cloud Storage.

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Qdrant

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Qdrant is a vector database that stores and searches high-dimensional data using advanced technology. Unlike traditional databases that store exact text or numbers, Qdrant works with vectors—mathematical representations of complex information. This makes it perfect for finding similar items based on meaning rather than exact matches.

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SinglebaseCloud

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SinglebaseCloud is a complete backend platform that lets you build AI applications with modern features. It provides a vector database for storing AI embeddings, a NoSQL database for regular data, user authentication, file storage, and AI tools like similarity search and RAG pipelines.

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Weaviate

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Weaviate is a database designed specifically for AI applications that need to understand the meaning behind data. Unlike regular databases that only match exact words, Weaviate can find information based on what you mean, not just what you type.

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Milvus

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Milvus is a database specifically built to store and search vector embeddings. When you use AI models to process text, images, or other data, they create numerical vectors that represent the meaning of that data. Milvus organizes these vectors so you can quickly find similar items.

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Langflow

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Langflow is an open-source platform for building AI applications through a visual interface. You create workflows by connecting building blocks called components. Each component performs a specific task, such as loading data, talking to an AI model, or storing information in a database.

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SnapLogic

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SnapLogic is an Integration Platform as a Service that connects your business apps and data sources together. Think of it as a bridge that lets different software talk to each other. Instead of hiring programmers to build custom connections, SnapLogic gives you ready-made building blocks called Snaps.

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Vellum

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Vellum is a platform that helps you create AI applications from start to finish. You can build chatbots, content tools, data analysis systems, or custom AI assistants. The platform works with all major AI models including GPT-4, Claude, and open source options.

Best 20+ Tools for Machine Learning Engineers in 2025