The interview process included:

• Recruiter calls to find the right organization.
• Hiring Manager Call.
• Data Science Technical Call.
• ML Systems Design Technical Call.
• Onsite loop.

I applied through the website for the open SWE, ML position. I had a few calls with recruiters to find the right organizational fit and negotiate location. The recruiters were actually really awesome at this stage. I tried to back out, thinking that it would not be a good fit, and they encouraged me to keep talking to different orgs to see if there was one that was right.

The call with the hiring manager was about making sure interests aligned.

The Data Science call was a stats/prob, ML/DM/DL knowledge quiz and an in-production ML system design problem applicable to Lyft.

The Systems Design call was an in-depth background chat and system design conversation related to ML.

The onsite loop was 2 ML-related interviews, 1 large-scale system design, 1 end-to-end coding problem on a laptop, and 1 manager conversation/soft skills. A lunch interview broke up the big day. All interviews had easy to medium difficulty questions but were evaluated very strictly for correctness, efficiency, and depth of knowledge. The laptop solution must run, be correct, show decent design, and if not perfect efficiency, identify where improvements can be made.

Recruiters communicated very well and always kept me aware of what was going on. All the interviewers were great. Travel arrangements were super easy and the options were nice.

The decision was relayed to me the next business day, and the offer arrived two days after that.

Coding and system design were typical questions you'd see on LeetCode or CareerCup.