ObvitreeChoosing a Transformer like it’s Optimus Prime time 🤖✨
#MachineLearning #Transformers #AIHumor #DataScienceLife #MLengineer #TechMeme #CodingHumor #AI
AI GeneratoristI am seeking a job as a computer science college graduate. I am open to being a machine learning engineer, data scientist, software engineer, or other similar role. I can work near Los Angeles or do remote work. I utilize Python, full-stack development, generative AI, and much more.
#FediHire #GetFediHired #JobSearch #LosAngeles #RemoteWork #MLEngineer #DataScientist #SoftwareEngineer #Python #FullStack #GenAI
MLE PathAI can help with interview prep—but don’t rely on it blindly.
➜ Use AI to refresh what you already know
➜ Ask specific questions with context
➜ Always ensure you understand the why behind the answer
AI should assist, not replace, real learning.
Want to break into ML engineering? The real path looks like this:
➜ Build a project for yourself—see if you enjoy it
➜ Fill in gaps with courses (now you know what’s missing)
➜ Build something useful for others
➜ Start applying & prepping
Actively building matters more than just studying.
When applying for MLE jobs:
➡ Stay organized—batch applications by similar requirements
➡ Prep for specific interview types
➡ Expand filters only if needed
Too much variation = burnout. Stay focused and sane!
After Senior MLE, your career can branch into 5 paths:
➡ Architect: Designing big systems
➡ Tech Lead: People-focused leadership
➡ Problem Solver: Tackling deep challenges
➡ Right Hand: Flexible leadership across roles
➡ Manager: Strategic leadership
What kind of ML leader do you want to be?
My student just crushed the ML System Design interview and landed a Meta E5 offer:
Base: $230k
Bonus: 15%
Sign-on: $80k
RSUs: $875k over 4 years, vesting quarterly with no cliff
Hard work and preparation pay off—congrats to him!
michabbbRevolutionary Development in Machine Learning Engineering 🔧
• 🤖 #NEO launches as world's first autonomous #AI #MLEngineer, transforming traditional ML workflows
• 🔄 System features parallel processing agents that handle entire pipeline from data prep to deployment, making development 10x faster
• 📊 Impressive performance metrics: Secured medals in 26% of tested #Kaggle competitions, matching #OpenAI benchmarks
• 💻 Tackles key #MachineLearning challenges:
- Data quality & preparation
- Model selection & optimization
- Computing resource management
- Deployment & monitoring
• 🎯 Real-world applications demonstrated through credit card fraud detection and book recommendation systems
• 🚀 Currently accepting early beta users through waitlist
Learn more: https://heyneo.so/blog
Your first ML design task: understand the question. 5 minutes of clarity will save you from an entire interview gone wrong. ⏳ #MLEngineer #SystemDesign
The best mentors? They don’t just give advice—they help you navigate the unknown. Build a mentorship team. 🧠 https://buff.ly/3TrECFv #TechMentorship #MLEngineer