Mentors who have worked at LinkedIn
Book a session with engineers and product people from LinkedIn on large-scale data and recommendation systems, and on how professional-network products are actually built.
Before you book a LinkedIn mentor
How do I choose the right LinkedIn mentor?
LinkedIn engineering sits at the intersection of distributed data infrastructure and recommendation systems, which makes its people unusually useful for anyone moving from general backend work toward data or ML-adjacent engineering.
What should I bring to a LinkedIn mentor session?
The interview loop places real weight on collaboration and on how you reason about ambiguous product requirements, not only on algorithmic correctness. Practising the conversation is worth as much as practising the code.
If your goal is your own job search, there is an obvious second use for a session here: someone who has worked on the product can tell you what recruiters actually see and filter on, which is more reliable than any list of profile tips.
For engineers moving toward data or ML work, ask specifically which parts of that transition were hard. Recommendation systems look like modelling problems from outside and turn out to be mostly data and infrastructure problems from inside, and knowing that early changes what you spend six months learning.
What people bring to these sessions
- Large-scale data infrastructure and recommendation systems
- Reasoning about ambiguous product requirements
- What recruiters actually filter on
- Moving from backend engineering toward data or ML
- Building products with strong network effects
1 mentor
- Kruti Shah — Staff Software Engineer at netflix. JavaScript, HTML5, CSS3