r/MachineLearningJobs

I'm looking for 1-2 interns (fully remote in India, part-time is okay) who can help me build some local/private AI apps for android (3-6 months). You can find some more details on what I want to build at invokal.com

Fair warning: These are all going to be free/no-ads apps on the play store which I'm building in my free time (call it stealth or whatever, I don't want anyone in my circle to know else I'll have to work with people I don't want to). Bootstrapped, no expected revenue so I won't be able to pay much - around INR 5k/month. I only need someone who understands the basics of AI and is willing to put in the effort. No PPO - I don't run a company. But you will be able to learn quite a lot - I've a Ph.D. in AI, multiple years of product experience and currently focusing on private AI and voice agents.

If you are genuinely interested, please share your CV at info@invokal.com with your LinkedIn profile. This is not my primary reddit, so do not expect any quick responses here. But I'll connect with the relevant candidates on LinkedIn - and no, I won't share my LinkedIn here publicly for reasons mentioned above. Once I connect with you on LinkedIn, you can judge for yourself if you wish to take this forward. I'm not forcing anyone to share their CV - it's your call.

Hi everyone,

I’m currently doing my Master’s degree and need to choose a topic for my research project. The project is restricted to one of two areas:

Federated Learning (FL)
Model Compression, specifically pruning and/or quantization

My main goal after graduation is to work in industry, rather than continue in academia, so I’m trying to choose the topic that would give me the most useful skills and experience for an ML/AI engineering career.

I’m particularly interested in hearing from people who currently work in the industry:

How widely is Federated Learning actually used in industry today?
Are companies actively hiring engineers/researchers with FL experience, or is FL still mostly an academic/research area?
How does the industry demand for FL compare with model compression, quantization, and pruning, especially for areas like edge AI, on-device ML, inference optimization, or ML systems?
Which of these topics tends to provide more transferable skills for an ML engineer?
If you were in my position, what factors would you consider when choosing between the two?

I’m not necessarily looking for a simple “choose X” answer. I’d really appreciate perspectives from people who have worked with either technology in industry, especially if you can share examples of how these skills are used in real-world projects or what kinds of roles require them.

Thanks!

r/MachineLearningJobs

Hiring Interns - 3rd or final years CS

Choosing between Federated Learning and Model Compression for an industry-oriented Master's research project