Mentors who have worked at Meta
Book time with engineers and product managers from Meta to work through interview loops, the bootcamp and team-selection process, and what performance and impact mean there in practice.
Before you book a Meta mentor
How do I choose the right Meta mentor?
Meta's loop is tight and signal-dense: fewer rounds, less tolerance for a slow start, and an explicit expectation that you keep talking while you work. Practising the pacing matters as much as practising the problems, and pacing is something you can only calibrate against another person.
What should I bring to a Meta mentor session?
The half of the process people prepare for least is what comes after the offer — how you end up on a team, and how much say you get. Ask a mentor about that specifically; it shapes the next two years more than the offer number does.
If you are already there or somewhere similar, bring a real performance-cycle question. Impact-based review systems reward legible, attributable work, and mentors who have written and received those reviews can tell you what reads as impact and what quietly does not.
What people bring to these sessions
- Pacing and communication in a short, signal-dense loop
- How bootcamp and team selection actually work
- What counts as impact in a performance cycle
- Product engineering versus infrastructure tracks
- Preparing for the product-sense round as a PM
3 mentors
- Vikas Malhotra — Tech Executive at amazon. Artificial Intelligence, GenAI, Java
- Nash Benjamasutin — meta. Understanding generative AI, Career guidance, Career transitions
- Lakshmi Mantena — Data Science Manager at ex-meta. Data science, Experimentation, Causal inference