I'm currently a third-year B.Tech student aiming for a Software Engineer (AI) or Backend Engineer position. Due to financial constraints, I have to find a job within the next 5 to 6 months. I have some familiarity with machine learning algorithms and data analysis but I'm not an expert yet. On the backend side, I'm proficient in Python and have built a simple Flask blog application to understand the basics.
I've been noticing that it's tough to land a data science or AI role fresh out of college without a specialized degree or significant experience, so I've decided to pivot to Backend Engineering to improve my chances of employment. However, after my Flask project, I realized I have a lot more to learn like Django or FastAPI, optimizing REST APIs, database management, and DevOps principles, which has been overwhelming considering my timeline.
I'm thinking about fully committing to Backend (Django/FastAPI and system design) to secure a regular Software Engineering job first. My ultimate goal is still to work where AI and Engineering meet. Here are my specific concerns:
1. Should I focus solely on mastering Backend skills (APIs, databases, DevOps), or is it practical to continue learning ML alongside?
2. Is it realistic to aim for a Backend role first and then transition into AI/ML later as a fresher in 2024/2025?
3. I see openings in GenAI/Automation roles that seem easier to get than standard SE jobs, but I'm worried this might be a short-term trap with low future career value. Is that a valid concern?
4. If I pursue Backend, is dedicating 2 hours a day to data structures and algorithms enough to pass screening rounds for these roles? Any suggestions on improving my roadmap would be appreciated!
2 Answers
Focusing on Data Structures and Algorithms (DSA) is definitely a solid move since it applies to many roles. Make sure your fundamentals are strong, and if you can, work on side projects when you have time. If your end goal is to work at the intersection of AI and backend, consider diving into systems programming and networking down the line to boost your chances.
Honestly, your situation is a bit challenging. It’s unlikely to secure an AI/ML position without experience or further education. Your backend experience seems limited too, especially if your biggest project so far is a blog app from a tutorial. Here's a suggested roadmap: start with Linux basics, get comfortable with Git and GitHub, learn SQL, and understand HTTP. Then choose between Django or FastAPI for your next project. Aim to have two solid projects under your belt, and try to deploy one. This is a baseline to stand out.
I appreciate your candid advice. I got a part-time data analyst offer, but I really want to dive into backend work and AI/ML. Should I keep focusing on my current projects or accept the offer?
Thanks for the advice! I'll prioritize my DSA practice.