Me postulé en línea. Acudí a una entrevista en Omnissa
Oferta aceptada
Experiencia positiva
Entrevista promedio
Solicitud
Acudí a una entrevista en Omnissa (Bengaluru)
Entrevista
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.
Preguntas de entrevista [1]
Pregunta 1
Two sum problem
Explain about Pytest hooks, fixturex, plugins
Discussion on Python Test Framework design
The overall process was very smooth and fast. Initial rounds were about DSA and Golang expertise. Hiring Manager round was about understanding the role's responsibilities in context of how it contributes to Omnissa's products and how my experience could play a part in it. The last, in-office, round was a combination of all the previous rounds.
Preguntas de entrevista [1]
Pregunta 1
- Average to hard level DSA problems
- Golang in depth discussion
- Deep technical dive into general challenges faced by the kind of products Omnissa offers.
Me postulé en línea. El proceso tomó 4 semanas. Acudí a una entrevista en Omnissa
Entrevista
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
Me postulé a través de una recomendación de un empleado. El proceso tomó 2 meses. Acudí a una entrevista en Omnissa (Bengaluru)
Entrevista
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
Preguntas de entrevista [1]
Pregunta 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