How Working Professionals Can Switch to an AI/ML - Mehvish’s AI Career Success Story

Thinking about switching to Artificial Intelligence but unsure if it is the right time or the right move? Many working professionals share the same question as industries rapidly adopt AI and ML technologies. Mehvish’s AI career success story brings a relatable perspective, showing that transitioning into this evolving field is possible with the right direction, practical learning, and a strong commitment to growth.

Like many professionals, Mehvish recognized the need to upgrade her skills to stay relevant in a technology-driven job market. Rather than viewing AI as overwhelming, she approached it as a strategic career opportunity. With structured training from DataMites, she focused on developing industry-ready capabilities that could support a smooth and confident career shift.

If you are a working professional considering a move into AI/ML, Mehvish’s story offers both reassurance and motivation. It highlights that with guided preparation, hands-on exposure, and consistent effort, stepping into the world of Artificial Intelligence can transform your career trajectory and open doors to future-ready roles.

Mehvish’s Journey from Software Test Engineer to AI/ML Engineer: Complete Q&A

Mehvish’s journey from a Software Test Engineer to an AI/ML Engineer highlights how structured learning and practical experience can open doors in the Artificial Intelligence world. Here, you can see valuable insights from her experience for anyone aiming to make a successful career transition into this fast-growing field.

1. Can you introduce yourself and your current role?

I am Mehvish Mulani, a computer science engineering graduate. After completing my degree, I worked at Accenture as a software test engineer. Over time, I developed a strong interest in data science and Artificial Intelligence, which motivated me to enhance my skills. With consistent effort and focused preparation, I secured a role as an AI/ML Engineer at Digitus Business Solutions, where I recently began my professional journey in this domain.

2. What inspired you to transition into AI and Machine Learning?

My curiosity about data and its potential to influence business decisions played a major role. I was fascinated by how meaningful insights can be generated from raw data and how these insights can guide organizations toward smarter strategies.

3. What kind of projects did you work on during your learning phase?

During my learning phase at DataMites, I worked on machine learning projects such as earthquake damage grade prediction, car price prediction, and lead categorization. These projects helped me understand the complete machine learning lifecycle, from data preprocessing to model development.

4. Did client and capstone projects make a difference in your preparation?

Yes, absolutely. Working on real-world and capstone projects strengthened my practical knowledge and allowed me to connect theoretical concepts with actual outcomes.

5. How many rounds were there in your interview process?

The interview process consisted of five rounds:

• MCQ-based written test
• Machine learning coding round
• Online technical interview
• In-office technical interview
• HR discussion

Each round evaluated different aspects of technical knowledge and problem-solving ability.

6. What kind of questions were asked during the technical interviews?

Most questions were based on my resume and projects. I was asked about algorithms such as decision trees and random forests, along with concepts like overfitting and underfitting in machine learning, bagging, and boosting, and how to handle them for better model performance.

7. Did the interviewers go deeper into your projects?

Yes, especially during the in-office technical round. They explored the reasoning behind model selection, implementation approaches, and the challenges faced during execution.

8. How did you learn about the job opportunity?

The PAT team at DataMites actively helped me by sharing suitable job openings and guiding me through the application process. Their support made it easier to apply for the role, and I was able to move forward confidently through each stage of the interview.

9. What technical skills should freshers focus on to become AI/ML Engineers?

Candidates should build a strong foundation in Python, particularly for data handling using Pandas and NumPy. Data visualization skills and core programming concepts such as loops, functions, and object-oriented programming are equally important.

10. How important is machine learning knowledge?

Understanding core algorithms is essential. Additionally, having basic to intermediate knowledge of large language models, embeddings, and generative AI concepts can provide a competitive advantage.

11. Which part of AI/ML do you find most interesting?

I enjoy working with data and uncovering the stories hidden within it. Transforming raw datasets into actionable insights that support business decisions is incredibly rewarding.

12. Which topics should candidates practice more because they are challenging?

Deep learning architectures such as CNNs, RNNs, and transformers deserve extra attention. A solid understanding of these concepts can significantly improve technical confidence.

13. How long does it typically take to prepare for an AI/ML interview?

Preparation timelines vary, but a focused plan of 3 to 4 months can be effective. For example, candidates might spend a few weeks on Python and SQL, another few weeks on statistics, and about a month mastering machine learning before exploring advanced topics.

14. Do projects really help in cracking interviews?

Projects are extremely important because companies want candidates who can apply knowledge practically. They also boost confidence and help candidates explain their approach clearly during interviews.

15. What strategies can improve interview performance?

Maintaining personal notes is very helpful. Reviewing concepts before interviews builds confidence and enables candidates to answer questions clearly and effectively.

16. What is your top advice for aspiring AI professionals?

Focus on fundamentals, practice consistently, and work on real-world projects. Confidence naturally follows when preparation is thorough.

Refer to these articles:

• Reinforcement Learning: Basics and Applications
• What is the Difference Between AI Engineer and AI Expert Course?
• Will AI Agents Replace Your Next Coworker? Exploring the Future of Work

Key Takeaways from Mehvish’s AI/ML Engineer Journey with DataMites

DataMites Success Stories continue to highlight real career transformations, and Mehvish’s journey from a Software Test Engineer to an AI/ML Engineer at Digitus Business Solutions shows how structured training, practical learning, and consistent preparation can help professionals successfully enter the Artificial Intelligence field.

1. Strategic Career Shift with the Right Training:

Mehvish transitioned from software testing to AI after recognizing her interest in data-driven technologies. By enrolling in DataMites, she built the technical skills needed to confidently move into a high-demand domain.

2. Industry-Focused Learning at DataMites:

The structured program at DataMites helped her develop strong knowledge in Python, machine learning, and data handling, ensuring she was prepared for real artificial intelligence industry expectations.

3. Projects Strengthened Her Interview Readiness:

Her work on projects such as earthquake damage prediction, car price prediction, and lead categorization demonstrated practical expertise, which became a major focus during technical interviews.

4. Strong Fundamentals Enabled Interview Success:

A clear understanding of core concepts, supported by the DataMites curriculum, helped her successfully navigate a five-round interview process.

5. Successful Placement at Digitus Business Solutions:

With the support of the DataMites placement team, Mehvish applied for a relevant opportunity and secured her role as an AI/ML Engineer at Digitus Business Solutions, marking a significant career milestone.

6. Consistency Built Confidence:

Regular practice, revision, and note-making helped her stay confident and communicate her knowledge effectively throughout the selection process.

7. Inspiring Path for Career Switchers:

Mehvish’s journey proves that with the right guidance, hands-on experience, and dedication, professionals from testing backgrounds can successfully transition into Artificial Intelligence careers.

Refer to these articles:

• How Nakshatra Secured Her First AI Engineer Job as a Fresher
• How Harsha Transitioned into an AI Product Manager Role? An Inspiring Success Story
• How to Switch from Graphic Designer to AI Developer - Sriram’s AI Career Success Story

If you are a working professional looking to upgrade your career and make a successful shift into Artificial Intelligence or Machine Learning, Mehvish’s journey is a perfect example of what’s possible with the right guidance. Like her, you can gain industry-ready AI/ML skills through hands-on projects, expert mentorship, and structured learning. 

DataMites is one of the best training institutes for professionals aiming to build a successful Artificial Intelligence career, offering a program designed to strengthen your Python, machine learning, deep learning, and data analytics skills while preparing you for real-world roles. With the right effort and the right training, your career transformation in AI/ML can start today.

DataMites Training Institute offers a 9-month Artificial Intelligence course to make learners industry-ready. Covering Python, machine learning, neural networks, and frameworks like TensorFlow and Keras, the course also provides hands-on experience with big data, cloud computing, and ethical AI. Accredited by IABAC and NASSCOM FutureSkills, it includes projects, internships, and career support to help learners excel in an Artificial Intelligence career.

DataMites offers Artificial Intelligence training across India through flexible online classes and 30+ offline centers, making quality AI/ML education accessible to everyone.

In Karnataka, students and professionals can enroll in the Artificial Intelligence course in Bangalore. Offline classes at prime locations provide hands-on learning, industry-relevant projects, and placement support to help learners confidently step into AI/ML roles.

In Maharashtra, Artificial Intelligence training in Pune is available at convenient centers, offering practical experience, real-world projects, and career guidance to prepare learners for a successful AI/ML career.