Alternatives
Products that do what 0-to-1 MLE Interview Playbook (2026) does
Ace ML Engineer interviews: theory, system design, prod ML
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Designing next-generation Artificial intelligence algorithms
2016
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Master FAANG DS interviews: ML, SQL, stats, A/B testing
May 2026 · amazon.com
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A couple of months ago, we left our jobs to build UpTrain AI, an open-source machine learning observability and refinement tool which helps users understand the performance of their models in production and improves them over time by identifying problematic data-points for retraining. Data drift, Distribution shifts, Model degradation, Edge cases - we have personally faced these problems in our previous organizations and have built a lot of tooling to solve them. We are building UpTrain so that others don’t need to build them and can solely focus on improving their ML models while we…
2023 · github.com
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Hey HN, I don’t know who else has the same issue, but: Textbooks often bury good ideas in dense notation, skip the intuition, assume you already know half the material, and get outdated in fast-moving fields like AI. Over the past 7 years of my AI/ML experience, I filled notebooks with intuition-first, real-world context, no hand-waving explanations of maths, computing and AI concepts. In 2024, a few friends used these notes to prep for interviews at DeepMind, OpenAI, Nvidia etc. They all got in and currently perform well in their roles. So I'm sharing. This is an open & unconventional…
Feb 2026 · github.com
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A practical playbook for designing production AI systems
Jun 2026 · topmate.io
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Ace AI Engineer interviews: RAG, agents, fine-tuning
May 2026 · amazon.com
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2021 · rentruewang.github.io
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Hey HN, Check out our technical paper here: https://arxiv.org/abs/2501.15627 and the video demo: https://www.youtube.com/watch?v=Op8hyLW7Z84 I’ve been obsessed with the art of the interview since I was in college. In my career I interviewed over 100 people and was interviewed from tech companies from startups to big tech and hedge funds. I built Neuraprep because I noticed something missing — while software engineers have leetcode.com and finance folks have quantquestions.com, other engineering domains (like ML, data science, MLOps) don’t have a go-to…
2025 · neuraprep.com
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Free, Infinity, Unlimited System Design Preparation with AI
27d ago · interviewdog.vercel.app
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Hey HN! When implementing an AI-powered feature for a project, we—and many people we've talked to—often reach a point where we have to choose an AI model but aren’t sure which one best fits our constraints or where to even start. Unfortunately, the advice to "just use chatgpt" is not always a good one. What if I want an open-source model? What languages does it support? What about context window size or the number of parameters? There are thousands of AI models already out there and many of them are perfect for certain problems. That’s why we’ve carved out this part of our product as a free…
2024 · app.elementera.ca
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Hi HN, My name is Othmane and I’ve been in the ML field (building and shipping models) for the last ~5years. Today, as many people out there, I come across new AI tools every week. However I was a bit surprised to see little to no mention of established AI vendors that existed before chatGPT and how most use cases are heavily biased toward content generation (text/image) or conversational AI (chatbots). I built a tool that helps you find the right AI solution/provider based on your use case. It uses a curated database of 100+ solutions from established vendors. It covers things…
2023 · preview.steerlab.ai
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Hey HN - spending time adding machine learning to your product is almost never worth it for startups. Formulating the problem, managing training data, training models, serving them, etc... for a 10% increase in some metric just isn't worth the time. Using rules + heuristics, although not optimal, does a pretty good job for a long time. There should be a better solution between rules & hardcore ML -- an 80/20 way to add ML to any product. Just slap it on top of the rules you already have, get that 10% gain, and never think about it again. I built an API that does just that. It's used by…
2021
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Hello HN! My name is Max, and I’m a co-founder at Lynx (https://uselynx.ai). We’re building an AI-powered incident resolution platform to help engineers debug and resolve on-call issues faster. If you’ve ever been paged in the middle of the night and had to spend hours piecing together logs, metrics, and code, we’d love your feedback. * The Problem * On-call hasn’t kept pace with modern engineering. Even with great observability tools, diagnosing incidents is slow because: - Systems are increasingly complex. - Logs, dashboards, and documentation are scattered. - Context often…
2025
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