Mimansa Jaiswal shared her experience of interviewing for researcher/engineer positions in the LLM/machine learning (ML) field last fall. Over 200 applications, 100 interviews, numerous rejections, and several offers—she decided to outline the entire process, as well as the resources she used. It’s extremely beneficial material, especially for those looking for a job in this field.
Link in the comments.
Summary (TLDR):
Startups:
Interview processes are unique and depend on the company’s development stage. Candidates may face 5–6 stages, including programming tasks (often from Leetcode), ML coding, testing fundamental ML knowledge, and cultural fit interviews. Startups may also require face-to-face interviews, multi-day work assignments, or extensive presentations. Processes are less standardized, and roles often include a wide range of responsibilities.
“Unicorns” (e.g., Anthropic, OpenAI, Scale AI):
More structured processes, but still vary from company to company. Candidates face interviews on programming (not always Leetcode-based), ML design, discussions related to LLM, and presentations. The number of stages can be substantial, especially when applying to multiple teams simultaneously.
Large tech companies (e.g., Meta, Amazon, Apple, Google, Microsoft):
Rigid and structured processes, often lasting from 1.5 to 2.5 months. Expect Leetcode-style interviews, ML system design, LLM research design, presentations, and behavioral interviews. Questions can be both general and role-specific.
Main interview components:
Programming tasks: knowledge of data structures and algorithms is tested, practice on Leetcode is necessary.
ML system design: evaluates understanding of system architecture and ability to develop solutions.
Presentations: candidates may present their previous work or research, demonstrating professionalism and communication skills.
Behavioral interviews: assess compatibility with corporate culture and approach to problem-solving.
Key differences by company type:
Startups are less predictable and may prefer candidates ready to take on diverse tasks. “Unicorns” look for specialists with narrow and current skills. Large tech companies adhere to formalized multi-stage processes and assess a broad spectrum of technical and soft skills. Each type of company has its unique demands and offers different opportunities, so it’s crucial to tailor preparation to the specific format.
Expected timelines:
The process can take from several weeks to several months, with possible delays during holidays or peak hiring seasons. Offers often require a quick response—usually within 7 days—requiring the ability to make swift decisions or negotiate a delay. It’s important to strategically plan overlapping processes and manage multiple timelines simultaneously.
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