Hi Sparsh,

Of course, I can guide how to transition from a Full Stack Engineer role into the AI/ML field and potentially find a job with a good package. Here are some steps you can consider:

1. Learn the Basics: Start by building a strong foundation in Machine Learning and Artificial Intelligence. Take online courses, enrol in MOOCs (Massive Open Online Courses) like Coursera, edX, or Udemy, and consider formal education like a master's degree in AI/ML if possible.
2. Projects and Practical Experience: Apply what you learn by working on AI/ML projects. Create your portfolio showcasing your work. This will be crucial when applying for new positions.
3. Specialize: AI/ML is a vast field. Identify the specific area within AI/ML that interests you the most, such as Natural Language Processing, Computer Vision, Reinforcement Learning, etc., and focus your learning and projects on that area.
4. Networking: Attend AI/ML meetups, conferences, and online forums to connect with professionals in the field. Networking can help you learn more, get advice, and potentially find job opportunities.
5. Open-Source: Contribute to open-source AI/ML projects. This not only demonstrates your skills but also helps you collaborate with experts in the field.
6. Online Courses and Certifications: Consider obtaining certifications like TensorFlow Developer or AWS Machine Learning to validate your skills.
7. Build a Strong Online Presence: Create a LinkedIn profile that highlights your AI/ML interests and projects. Share your work on GitHub or other platforms. This can attract potential employers.
8. Update Your Resume: Tailor your resume to showcase your relevant skills and experience, even if it's minimal at this point. Highlight transferable skills and your commitment to transitioning into AI/ML.
9. Apply for Jobs: Start looking for entry-level AI/ML positions or internships in companies that are open to hiring candidates with a strong foundation and willingness to learn.
10. Interview Preparation: Once you start getting interviews, prepare extensively. Study common AI/ML interview questions, practice coding challenges, and be ready to discuss your projects.
11. Stay Persistent: Transitioning into a new field can be challenging, but persistence is key. Don't get discouraged by rejections and keep improving your skills.

Regarding mentorship, I can provide guidance and advice.

Switching to the AI/ML field is possible with dedication and a well-planned approach. It may take time, but with continuous learning and effort, you can land a job with a good package in the AI/ML domain. Good luck with your career transition!

Feel free to connect with me on LinkedIn: Abhilekh Verma | LinkedIn