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      Omnissa

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      Senior Member of Technical Staff Interview

      May 5, 2025
      Anonymous employee
      Bengaluru

      Other Senior Member of Technical Staff interview reviews for Omnissa

      Sr Member of Technical Staff Interview

      Apr 30, 2026
      Anonymous employee
      Accepted offer
      Positive experience
      Difficult interview
      Accepted offer
      Positive experience
      Average interview

      Application

      I interviewed at Omnissa (Bengaluru)

      Interview

      3 technical rounds for Horizon Perfomance Team Most questions on Automation (Python) few questions on OS Fundamentals (Threading, Process, OS tuning) Scenarios base Questions on Perfomance, like if x CPU and y Memory is giving xy perf for an application what impact wil : x+1 CPU , x-1 CPU x+1 CPU and y+1 mem etc have on the application overall more openended questions to understand the thought process of the individual.

      Interview questions [1]

      Question 1

      Two sum problem Explain about Pytest hooks, fixturex, plugins Discussion on Python Test Framework design
      Answer question

      Application

      I applied online. The process took 4 weeks. I interviewed at Omnissa

      Interview

      The interview was brief enough as well as transparent too, there was around 4 rounds of interview for me including a leadership interview, the panel seems to be have cross team as well, and the I find the interview pretty decent good and fair

      Sr Member of Technical Staff Interview

      Aug 22, 2025
      Anonymous employee
      Bengaluru
      Accepted offer
      Positive experience
      Difficult interview

      Application

      I applied through an employee referral. The process took 2 months. I interviewed at Omnissa (Bengaluru)

      Interview

      There were total of 5 to 6 rounds which tested technical competence. 1. Tech round (1hr+). discussing about the projects and AI/ML/GenAI algorithms from the fundamentals. (math and its intuitive) 2. Coding round. (1hr+) (starting from list comprehension to implementation of ML algorithms without using inbuild func, SQL (correlated queries, window fns etc), pyspark, HDFS concepts, fundamental ML concepts 3. Technical deep dive of AI/ML projects 4. Problem solving round (non-coding) (1hr)- core probability & statistics, distributed systems 5. Managerial round - Leadership + Tech + Behavioural 6. In-person interview (3hrs) - you meet with the team for another couple of rounds of discussion

      Interview questions [1]

      Question 1

      Implementation of Agentic AI applications, Agentic RAG, NL2SQL, LLM (training + inference + quantization), Classical ML Algos (training + inference), Mathematical intuition of all the AI/ML algos, probability & Statistics etc
      Answer question