J'ai passé un entretien chez Walmart Global Tech (Sunnyvale, CA)
Entretien
The interview process begins with an initial screening, then followed by 2 rounds of onsite interviews: 1st onsite has 2 meetings, 2nd onsites has 4 meetings, each onsite include technical assessments and multiple rounds of interviews.
J'ai passé un entretien chez Walmart Global Tech (Bengaluru)
Entretien
interviewer asked statistics questions,
interviewer asked Ads based probability questions.
interviewer asked One coding question based on array which was medium level
person ideally should know naive bayes and solve probability puzzles.
Questions d'entretien [1]
Question 1
interviewer asked One coding question based on array which was medium level
J'ai postulé via la recommandation d'un employé. Le processus a pris 3 mois. J'ai passé un entretien chez Walmart Global Tech (Bengaluru) en févr. 2025
Entretien
4 Technical ML design rounds. 1 round with Director. All interviews were originally scheduled for 1 hour but 3/5 interviews overflowed to 1.5 hours. No coding assessment done. Each subsequent interview was scheduled contingent on the positive feedback from the earlier interviews.
All interviews went well but there was no offer made and no explanation was provided. Pinged the Director on Linkedin to politely check on the feedback. Director replied saying he is surprised to learn the outcome and will have recruiter contact me shortly. Recruiter contacted 1.5 months later checking if I am still interested.
Questions d'entretien [2]
Question 1
Design a Catalogue policy violation detection system
J'ai postulé via un recruteur. J'ai passé un entretien chez Walmart Global Tech (Sunnyvale, CA)
Entretien
Interview process was standard. First interview was with the hiring manager and subsequently four more interviews in combination of data structures and ML/CV. Most of the interview was ML heavy, from basic ML questions to the questions related to the team's project.
Questions d'entretien [1]
Question 1
What is contrastive loss and how it works. Nearest neighbor search.