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At Deep Tech Stars, we have been working closely with AI developers for over a decade, and we also help companies find and hire the right AI devs for their requirements. In this session, we will focus on best practices related to the interview process, how to outperform other interviewees to become the top pick, and how to land the right offer for you.

Note: This is the second part of a 2-part series. In the first part, we covered the best practices on how to find and apply to top AI jobs and start getting interview calls. If you missed that session, no problem, you can still attend this one and then catch up on the first part later once it is uploaded to our YouTube channel: https://www.youtube.com/@deeptechstars

AGENDA
8:00 PM: Welcome note
8:05 PM: Interview process reality check - What's changed and what has stayed the same
8:15 PM: What interviewers are looking for - Deep dive into the recruiter mindset
8:30 PM: Assignments and projects - How to leverage these to outperform other candidates
8:45 PM: Getting the offer letter - Cultural/HR/Behavioural interview, green and red flags, closing the deal
8:55 PM: What to do after accepting the offer letter
9:00 PM: Resources to help with your job search, and conclusion

SPEAKER
Nihal Kashinath - Founder of Deep Tech Stars
LinkedIn: https://www.linkedin.com/in/nihalkashinath/

FEE
This workshop is FREE to attend but seats are limited and available on an invite-only basis. Prior registration is required for receiving an invitation, as per the below process.

REGISTRATION
To register, please do BOTH of the following:
1. Fill in your details in this Luma form by clicking "Request To Join"
2. If you haven't done so already, download the Deep Tech Stars app here:

Please reach Nihal at 9663374431 if you need any clarifications or have any challenges in registration.

We look forward to seeing many of you there!

Related topics

Artificial Intelligence
Artificial Intelligence Applications
Artificial Intelligence Machine Learning Robotics
Artificial Intelligence Programming
Machine Learning

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