Hello everyone,
I'm reaching out to this community seeking advice and insights as I consider a significant career transition. Currently, I am working in software engineering, but I've recently completed my master's degree with a core focus on Reinforcement Learning and Artificial Intelligence.
Throughout my academic journey, I've developed a strong passion for AI/ML, and now, I'm eager to pivot my career in this direction. While I've gained substantial experience in software development, I believe that transitioning to a team more aligned with AI/ML will allow me to fully utilize my skills and contribute more meaningfully to the field.
I understand that networking plays a crucial role in such transitions. However, I'm looking for guidance on the best practices for connecting with AI/ML engineering managers. I am particularly interested in learning about:
Additionally, I'd love to hear any personal stories or experiences about making a similar transition. What were your challenges, and how did you overcome them? How did you leverage your previous experience during this shift?
I appreciate any advice or connections you might offer. Please feel free to reach out to me directly if you're open to a conversation.
Thank you for your time and support!
Best regards
Strategies to demonstrate my competence and enthusiasm for AI/ML, despite my primary experience being in software engineering.
Tons of opportunities to do this:
LinkedIn is often the first thing people think about when it comes to networking, so here are some best practices for LI networking: https://www.jointaro.com/question/43hWWtHiyaWA7FTv97IS/connect-with-senior-engineers-on-linkedin-you-want-to-learn-from/
Effective ways to initiate conversations with AI/ML leaders, especially when coming from a different technical background.
Here are the ways I would go through, organized by effectiveness:
When it comes to general networking, I highly recommend this: [Masterclass] How To Build Deep Relationships Quickly In Tech
For resources around the life of an MLE, check these out:
Insights into the challenges and expectations specific to AI/ML teams that I might not be aware of coming from a different specialization.
Although I don't have a background on a AI/ML team, you can ask the EM about the kinds of projects their team is responsible for and what the team KPIs are.
By getting a history of the team's projects, you'll be able to dive into a deeper conversation with the EM about the particular challenges from that project and the problem that the project was trying to solve.
I would also advise talking to multiple EMs so you can triangulate the expectations among different teams.