The most useful thing about Shrushti Kale’s AI and machine learning placement is how ordinary its ingredients are, and how early she started applying them. A B.Tech Computer Science graduate specialising in Artificial Intelligence and Data Science at Parul University, and admitted through the ACPC scholarship process, she reached a machine learning role at the Hyderabad fintech company Jocata not by chasing a company but by building capability. Her guiding principle is one she repeats often.
Don’t learn just to get into a company. Learn to create an impact.
– Shrushti Kale
Rather than beginning placement preparation late, Shrushti built her technical foundation years earlier, starting with Data Structures and Algorithms, moving through backend web development with Django and FastAPI, teaching herself data science and statistics, and finally specialising in machine learning. That deliberate sequence is worth following in its own right, and it is set out step by step in how to become a machine learning engineer. What matters for her story is that by the time placements began, she was not preparing from scratch; she was consolidating years of work.
Learning by Building: Projects That Mattered
Shrushti kept every concept tied to a project, and two stood out. The first was an AI-powered university bus tracking and prediction system that used machine learning to predict bus arrival times and estimate delays, a genuinely useful application of predictive analytics. The second was a data analytics and fraud-detection project, in which she analysed datasets to identify suspicious patterns. That second project is a neat foreshadowing of where she ended up: Jocata builds AI systems for exactly this kind of financial fraud detection, so her academic work mapped directly onto her employer’s domain. In interviews, she did not just list the technologies; she explained the problem, the architecture, the algorithms, and the results, which is what made the projects land.
Why Internships Made the Difference
Two internships strengthened both her skills and her confidence. The first, in web development at Enpora, taught her how software is designed, built, and deployed professionally, exposing her to real coding practices, teamwork, and debugging. The second, a remote data analytics internship at Zipro, showed her how organisations turn data into business decisions and how professional remote work operates. She is emphatic about how much these mattered, and about not letting distance or discomfort get in the way.
If you get an internship, even if it is far from home or outside your comfort zone, accept it. Every new experience helps you grow, personally and professionally.
– Shrushti Kale
The Placement and Stepping Outside the Comfort Zone
There are always some decisions in life that are hard, and the placement offer of Jocata happened to be one of such for Shrushti. The role was in Hyderabad, away from her home. She took time, analysed the work culture, and discussed it with her parents, who then supported her, as it would benefit her career. It is a small illustration of a larger point she makes: that growth often begins precisely where comfort ends, and that a considered willingness to move for the right opportunity is part of building a career.
The Role of IMPACT Training
IMPACT Training has helped many students, and Shrusti happens to be one of them. The IMPACT Training programme of Parul University is part of the placement preparation. Through this training, she gave her honest review that she gained communication skills, one of the valuable parts of the interview, appreciating its practical emphasis on speaking confidently and expressing ideas clearly in interviews. Strong communication, she believes, is the skill that lets technical knowledge actually be seen, a complement to expertise rather than a substitute for it.
Frequently Asked Questions
How do you get an AI or machine learning placement as a student?
By building genuine capability rather than only preparing for interviews: mastering fundamentals early, working on real machine learning projects, completing internships, and being able to explain your work clearly. Shrushti Kale reached her machine learning role at Jocata through years of self-directed learning, two internships, and projects such as an ML-based bus-prediction system and a fraud-detection project, not through last-minute preparation.
How important are internships for getting placed?
Very. Internships build technical competence, confidence, adaptability, and communication, and they often become a resume’s strongest highlight in interviews. Shrushti completed a web-development internship and a remote data-analytics internship, and credits both as major factors in her placement, advising students to accept internships even when they require stepping outside their comfort zone.
Do machine learning projects help in placements?
Strongly, especially when you can explain them well. Recruiters value not just what technologies a project used, but the problem it solved, the design decisions behind it, and its results. Shrushti’s projects, including an AI bus-prediction system and a fraud-detection analysis, were among the most discussed topics in her interviews precisely because she could explain her reasoning.
