How Andal Cracked Her First ML Engineer Job as a Fresher

Andal’s journey from a fresher to landing her first Machine Learning Engineer role highlights how practical learning, hands-on projects, and mentorship helped her build the skills and confidence to start her career in machine learning.

Priyanka BR Priyanka BR
Sep 29, 2026 Updated: Sep 29, 2026
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How Andal Cracked Her First ML Engineer Job as a Fresher
Datamites AI/ML Engineer course success story by Andal

Andal’s journey from a career gap to becoming an Associate ML Engineer shows how continuous learning and determination can create new career opportunities. Her interest in Data Science led her to explore Machine Learning and take a confident step toward a career in technology.

During her Career Transition to Machine Learning, Andal built skills in Python, SQL, and Machine Learning through structured learning, practical projects, and interview preparation. For those exploring how to start a career in Machine Learning, her experience highlights the value of mentorship, hands-on projects, mock interviews, and consistent practice.

How Andal Started Her Machine Learning Career with DataMites

Andal’s journey from a graduate with a career gap to pursuing a Machine Learning career highlights the value of consistent learning, practical projects, and mentorship. Through DataMites, she built her skills and confidence to enter the Machine Learning field.

Q1: What was your journey before joining DataMites?

My name is Andal, and I am currently working as an Associate ML Engineer at Trinity Mobility Private Ltd. After completing my bachelor’s degree, I had a gap in my career. Later, I learned about career opportunities in Data Science and discovered DataMites. I decided to join the full-time course, where I learned Python, SQL, Machine Learning, and other Data Science concepts that helped me move toward my career as an Associate ML Engineer.

Q2: Why did you decide to join DataMites?

I wanted to build my career in Artificial Intelligence and Machine Learning, so I decided to take structured training. Before joining, I had some doubts about whether I would be able to learn all the technical concepts. But the confidence and guidance I received from the DataMites team encouraged me to take the next step and continue with the course.

Q3: What did you learn during your DataMites course?

During my journey, I learned Python, SQL, Machine Learning, and other Data Science concepts. I kept practicing the concepts and taking notes so that I could understand them better. I also worked on different projects, which helped me connect what I learned in the sessions with practical applications.

Q4: What was your learning experience with DataMites?

My learning experience at DataMites was really helpful. I attended the course through the online mode and also used the recorded classes for studying and revision. I used the recordings to take notes and prepare myself. My mentor and the entire team guided me throughout my journey, which helped me a lot.

Q5: Did you find learning Python and Machine Learning difficult?

Initially, I found Python and Machine Learning challenging because of my background. However, the DataMites team and mentors gave me confidence and encouraged me to keep learning. Their guidance helped me overcome my doubts and continue progressing.

Q6: How many projects did you work on during your internship?

I worked on four capstone projects and one client project. The four capstone projects were really helpful because each project was based on different topics. Through every project, I learned something new. The client project was also very useful because it gave me an opportunity to understand how things are done in a real world working environment.

Q7: How did the projects help you in your Machine Learning career?

The projects helped me apply concepts beyond theory and gain practical experience. The capstone and client projects also prepared me for the Machine Learning interview by giving me exposure to real-world work.

Q8: Did your projects help you crack the interview at Trinity?

Yes, my projects helped me a lot in cracking the interview. Since the role at Trinity was related to Machine Learning, the Machine Learning projects I had already worked on gave me practical experience. I could relate my previous project work to the role and answer questions with more confidence.

Q9: How many mock interviews did you attend at DataMites?

I attended four mock interviews. In the first mock interview, I did not pass. But I did not stop there. I kept trying and thought about why I had not cracked it. I worked on my preparation and continued improving. Finally, in my fourth attempt, I cracked the mock interview.

Q10: How did the mock interviews improve your interview preparation?

Every mock interview helped me improve my performance. After each attempt, I understood where I needed to work more. The repeated practice helped me become more comfortable with the interview process. By the time I attended the actual interview, I had already experienced the pressure of mock interviews, so it helped me prepare better for the real interview.

Q11: How did the PAT team support you during your interview preparation?

The DataMites PAT team supported me throughout my journey. Whenever I did not clear a mock interview, they helped me schedule the next attempt and guided me with my doubts and preparation. Their continuous support helped me improve and stay focused.

Q12: How did you prepare for the technical interview?

First, I focused on Python. I learned Python and kept practicing it. Then I worked on SQL and continued practicing SQL as well. For Machine Learning, I used Kaggle to keep working on different problems and maintain regular practice. Throughout my preparation, I kept taking notes, learning from my mistakes, and working on the areas where I needed improvement.

Q13: Did DataMites help you with your LinkedIn profile?

Yes, the team also helped me with my LinkedIn setup. They guided me on how to improve my profile and what kind of things I should post. This helped me understand how to present my skills and learning journey professionally on LinkedIn.

Q14: How many interview rounds did you have at Trinity?

There were two rounds in total. The first round was an assessment test. They provided me with a set of data and asked me to work on it. During the assessment, I worked on Machine Learning model creation, and they also questioned the candidates individually. After that, I was selected for the second round.

Q15: What advice would you give to freshers who want to enter Data Science or Machine Learning?

I would tell freshers to confidently choose DataMites and choose whichever field they are interested in. The team will help you throughout your journey. For interview preparation, do your best and keep working on your skills. Do not lose hope if you fail at something. Keep moving forward, keep practicing, and keep learning from your mistakes.

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Andal’s Key Takeaways on Building a Career in Machine Learning

Her journey highlights how structured learning, practical projects, mentorship, interview preparation, and consistent effort can help build a career in Machine Learning.

  • Background: Andal completed her bachelor’s degree and had a gap in her career before entering the technology field.
  • Career Gboal: She wanted to build a career in Data Science and Machine Learning.
  • Training Choice: With the growing demand for IT courses, Andal chose DataMites for structured training that helped her develop the technical skills needed to pursue a career in Machine Learning.
  • Technical Skills: She learned Python, SQL, Machine Learning, and other Data Science concepts during her training.
  • Mentorship Impact: DataMites mentors guided her throughout the learning journey and helped her overcome doubts about learning technical subjects.
  • Practical Learning: She completed four capstone projects and one client project, gaining practical exposure beyond theoretical learning.
  • Interview Preparation: She regularly practised Python, SQL, and Machine Learning concepts and used Kaggle to strengthen her skills.
  • Mock Interviews: She attended four mock interviews and continued improving after not clearing her first attempt.
  • PAT Support: The DataMites PAT team helped her schedule mock interviews, resolve doubts, and prepare for job opportunities.
  • Resume Development: She received guidance on creating her resume and improving her LinkedIn profile for professional opportunities.
  • Interview Experience: Her first client interview involved a technical assessment, Machine Learning model creation, and a face-to-face technical round.
  • Career Breakthrough: Her preparation and practical experience helped her begin her career as an Associate ML Engineer.
  • Advice for Learners: Andal encourages aspiring Machine Learning professionals to stay confident, keep practising, learn from setbacks, and never give up.

Andal joined DataMites to build a career in Machine Learning after a career gap. Through structured training, she developed skills in Python, SQL, and Machine Learning while gaining practical exposure through capstone and client projects. Mock interviews, mentor guidance, and PAT support helped her strengthen her interview preparation and confidence. Her consistent efforts helped her take her first step toward a career as an Associate ML Engineer.

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