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SME India : Machine Learning (Instructor)

6 - 11 years

6 - 10 Lacs

Posted:2 weeks ago| Platform: Naukri logo

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Job Type

Full Time

Job Description

Part Time Subject Matter Expert - Machine Learning The name Interview Kickstart might have given you a clue. But here s the 30-second elevator pitch - Interviews can be hard. And when it comes to the top tech companies like Google, Apple, Facebook, Netflix, etc., they can be downright brutal. Most candidates don t make it simply because they don t prepare well enough. InterviewKickstart (IK) helps candidates nail the toughest tech interviews. At IK, current and former hiring managers at these top companies take candidates through an intense interview prep course to make them completely ready to crack the toughest interviews. We are looking for Machine Learning Engineers - part-time Instructors .This role will provide opportunities to network with other experts, understand learner issues and contribute to the Machine Learning community at large. Responsibilities: Constantly improve the session flow and delivery by working with other instructors and subject matter experts As our SME - Instructor , you would work closely with our students and participate in delivering classes , do 1:1 technical coaching sessions (doubt clearing) and mock interviews. Have regular discussions with IK s curriculum team in evolving the ML curriculum To ensure the highest quality of content, we expect our partner to spend at least 6-8 hours a week on this project. The topics to cover are majorly in ML Mathematics and ML Core Topics. Requirements: Minimum 6 years of experience in tier-1 Tech companies as an ML Engineer or Scientist Excellent understanding of large-scale ML systems Ability to simplify complex topics and explain them in an engaging manner High levels of empathy to understand the challenges faced by students and willingness to help them out Should be willing to work on weekends/evenings and be available as per the Indian time zone PhD in Computer Science/Applied Mathematics/Statistics is preferable.

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