I applied online. The process took 4 weeks. I interviewed at Fractal in Nov 2018
Interview
There were 5 rounds overall.
1. Coding round - Questions from data structures were asked. There were total 3 questions to be solved in 1 hour.
2. Technical telephonic discussion - It was with one of the senior data scientists in Fractal. The questions were mostly related to Machine Learning and there were some resume related questions.
3. Technical Skype round - In this, questions were based on string manipulation algorithms and case studies. ML related questions were also asked
4. HR round - This round mainly included basic HR questions.
5. Telephonic Discussion with AI/ML head - This round was mainly to check how much in-depth knowledge the candidate is having. The questions were based on different ML techniques and some real life scenarios.
There was 1 final aptitude test to be completed at the end. It had 75 questions to be done in 70 min.
The overall interview experience was good and smooth.
Interview questions [1]
Question 1
In initial screening rounds, they are focussed on how much knowledge we possess on different ML techniques. In later rounds, they asked different case study questions based on real life scenarios.
Thank you for sharing your experience in the recruiting process with Fractal. We appreciate your feedback and are pleased to hear our goal of a positive candidate experience was met. Congratulations on the offer & welcome to the family.
Fractal HC Team
Other Data Scientist Interview Reviews for Fractal
I attended a one-hour AI/ML interview focused on Machine Learning fundamentals and practical applications. The discussion covered ML algorithms, model selection strategies, evaluation metrics, feature engineering, optimization techniques, and deployment challenges. The interview included conceptual, problem-solving, and scenario-based questions to assess both theoretical understanding and practical experience in AI/ML.
Interview questions [1]
Question 1
The interview was primarily focused on Generative AI concepts and their practical applications. Questions covered Large Language Models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG), vector databases, embeddings, fine-tuning techniques, and AI agent frameworks. The interviewer also asked scenario-based questions on designing GenAI solutions, selecting appropriate architectures for different use cases, handling hallucinations, evaluating model performance, and addressing scalability, security, and deployment challenges. Additionally, there were discussions around real-world implementation of GenAI applications, model optimization, and best practices for building production-ready AI systems.
Good and Short interview process
3 round of interview
1 take home assignment
1 round technical
1 round HR
each interview last 30min
Interviewer were supportive and helping
Whole interview take 1 week
Mildly challenging and nice. I would probably reduce number of rounds, i had 4 of them. The first two were technical and third one was managerial. The last round was done for cultural fit.
