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Deep-ML released interview preparation guides for Machine Learning Engineer and Quantitative Researcher roles at Jane Street, covering study topics and resume projects.
The author shares ML interview preparation tips and recommends Chip Huyen's books and resources for candidates.
Announces the free availability of the 'Competitive Programmer’s Handbook', covering 30 important DSA topics for tech interview preparation.
A tweet highlights how @neetcode1 built a successful YouTube channel by documenting his own interview prep, and how getting into Google afterward gave his channel credibility and exponential growth.
Deep-ML launched a premium feature for interview preparation tailored to Anthropic Researcher and Machine Learning Engineer roles, including project building and round-by-round guidance.
Alisa Liu is joining OpenAI and has publicly shared her interview preparation notes and study resources for free.
Alisa Liu is joining OpenAI next week and shared a blog with job-search notes, including LLM and math resources.
Recommend a continuously updated AI system design learning guide that covers 110 real interview questions and answer frameworks, including core tech stacks like RAG architecture, Agent, multi-tenant isolation, and large model selection.
A comprehensive cheat sheet of 12 system design patterns for technical interviews, including signals, building blocks, and deep-dives for each pattern, based on 200+ interviews across top tech companies.
The author announces a free AI Interview Prep Module inside their multi-agent workflow sandbox, listing 42 interview questions for GenAI and Agentic AI roles with standout answers.
An AWS engineer has created free, structured notes summarizing both volumes of Alex Xu's System Design Interview book, available on GitHub and via the website Pagefy.io.
Noeth is an AI tool for coding interviews that allows users to bring their own API key.
A shared link to a Language Models Interview Handbook, likely containing study materials for AI/ML technical interviews.
A GitHub repository containing comprehensive system design interview notes based on Alex Xu's bestselling books, covering topics like scaling, consistent hashing, and distributed systems.
A shared resource linking to an interview preparation playbook focused on RAG evaluation and testing for LLMs.
The article claims that 90% of AI system design interviews in 2026 revolve around just 11 repeated concepts.