With this program, you will learn through design patterns and get plenty of practice exercises with live instructor guidance. It features a 16-week highly structured curriculum to help you navigate coding, system design, machine learning, and behavioral interviews with interview-focused content. Interview Kickstart’s Machine Learning Interview Course is the first-of-its-kind, ML-specific tech interview prep program designed and taught by FAANG+ instructors. Moreover, interview-relevant insights are usually missing from such content, as they cater to a more general audience, i.e., people who want to learn ML instead of those who want to prepare specifically for an interview. The information is unstructured and often outdated. However, navigating this vast ocean of material can become overwhelming. There are many ML Engineering resources available on YouTube and other e-learning websites.

Relying only on past knowledge and experience to crack this interview might work for some, but most will need a structured approach to help them prepare. Apart from ML algorithms, you need to be proficient in general coding, software system design, and, most importantly, ML system design.Īn average ML Engineer interview consists of 5-8 rounds. On top of that, the interviews are very intensive, especially at top tech companies like FAANG. Not exactly! Such a high demand for talent also comes with competition at every seniority level. With ML startups popping up daily in diverse fields like search, recommendation, advertisement, finance, healthcare, news, logistics, automotive, and even creative fields, the demand for ML Engineers will only rise in the future. Top tech companies like Meta, Google, Apple, Amazon, etc., are expanding their ML teams in a big way and are willing to pay top dollar to attract the right talent. There is a massive demand for ML Engineers – more than 40,000 LinkedIn job postings in the US and worldwide (as of October 2022).

What it takes to crack Machine Learning Engineer interviewsįrom being an emerging role in 2017 with about 1800 job postings on LinkedIn, Machine Learning Engineer has risen to the Top 10 best roles in 2022.

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