Quit my job to break into AI
I am 29YO and have been working as a software engineer in big tech for ~4 years. My day job feels like a lot of meaningless work and I find it difficult to put in effort. It is largely because I would rather spend my time going through the list of books and courses I listed below and eventually build a project that has been on my mind for the past year.
I tried to do this with my full-time job, but it was pretty difficult as my job is very demanding. There's a lot of late nights and deadlines to meet. It gets worse every passing month and I just would rather not be here.
For the past year, I have been flirting with the idea of quitting my job to self-study and break into AI. Ideally, I would start with fixing my fractured math background(in progress) as I genuinely believe that a strong math background would transform the way I think about and approach problems. I listed several courses and books that I want to go through. I would also build projects and write blog posts to solidify my understanding.
Eventually, I want to get to a point where I can reproduce ML papers and build my capstone project. For the capstone, I want to build a real-time computer vision model on an edge device i.e. Nvidia Jetson Nano that can play games competitively. This will be similar to the work OpenAI did on DOTA 2(as much as I can do for one person) but for a different game. This will most likely be published to github.
Once this plan concludes, there are multiple paths I can take:
- Start an AI startup building products that I care very deeply about.
- Join an AI startup or big tech(Meta, google, Anthropic, etc). I am not working for another person/company except I deeply care about the work. I will not be drained again.
- Apply for PhD programs. I can strengthen my application by writing a paper based on my capstone project and attempting to get it published in a peer-reviewed journal.
I will be giving my notice to my manager sometime in April. I currently have saved up about 2.5 years(can stretch to 3) of living expenses and I can also look for a part-time job if necessary.
Here's the study plan:
Year 1
- Spring 2025 Arc (Jan - April) (I still have a full-time job during this period)
- Mathematical Foundations 1 (in progress)
- arithmetic, variables and graphs, algebra, geometry.
- Mathematical Foundations 1 (in progress)
- Summer 2025 Arc (May-August)
- Mathematical Foundations 2
- quadratics, logarithms, trigonometry, polynomials, basics of limits, derivatives, integrals, complex numbers, vectors, probability, and statistics.
- Mathematical Foundations 3
- limits, derivatives, integrals, optimization, particle motion, and differential equations. Dive deeper into complex numbers, vectors, matrices, parametric and polar curves, probability, and statistics.
- The Elements of Computing Systems, second edition: Building a Modern Computer from First Principles (in parallel with items above)
- Project and blog posts (may carry over onto Fall 2025)
- TBD
- Mathematical Foundations 2
- Fall 2025 Arc (September-December)
- carried over items
- Proofs course + An Introduction to Mathematical Reasoning book
- Linear Algebra course
- Mathematics for ML
- Multivariable Calculus
- Project and blog posts (may carry over onto Spring 2026)
- TBD
Year 2
- Spring 2026 Arc (January-April)
- carried over items
- Probability & Statistics
- Differential Equations
- Reproduce ML papers to practice all the maths I've learned so far
- Project and blog posts (may carry over onto Summer 2026)
- TBD
- Summer 2026 Arc (May-August)
- carried over items
- Programming Massively Parallel Processors: A Hands-on Approach (in parallel with items above) - This is to learn CUDA.
- One or more of the below (will most likely be carried over to summer 2026)
- Deep Reinforcement Learning UC Berkely
- Andrej Karpathy's Neural Networks: Zero to Hero Series
- Reproduce ML papers related to my capstone project
- TinyML: Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers - this will help for my capstone project
- Fall 2026 Arc (September-December)
- carried over items
- Begin capstone ML project
- Spring 2027 Arc (January-April)
- Finish up all carried-over items
Any suggestions on this plan/timeline?
Also, if there's anyone on a similar path, DM me so we can keep each other accountable!
Edit:
Thanks for all the wonderful comments and tips! I will make adjustments and have a more realistic timeline of 1 year. I will choose a project and go top-down.
Also, the majority of the comments seem to be too focused on the "getting a job in ML" part when that isn't even my preferred outcome. I mentioned earlier in the post that I have ideas of projects I would like to build and then start a startup. If all else fails, I will go back to look for a job.
Anyway, thank you all for the suggestions! Much appreciated.