AI Research assistant ML & EE

I’m looking for an agile researcher who can jump between Machine Learning, Deep Learning, Computer Vision and core Electrical Engineering work without missing a beat. Most of what I send your way will sit at the intersection of data-driven algorithms and classic engineering analysis: think rapid literature scans, model prototyping in Python (TensorFlow / PyTorch), quick-turn MATLAB or Simulink simulations, and concise technical write-ups that translate results into clear engineering insights. The project stream is firmly rooted in Electrical Engineering, so an ability to frame ML findings in terms of circuits, signal behaviour, power-system performance or similar contexts is essential. Speed matters—I often need same-day clarifications or iterative tweaks—yet I never compromise on code readability, sound methodology or properly cited sources. Competitive, value-for-money offers will weigh heavily in my selection. Deliverables on each mini-task typically include: • Clean, reproducible code with comments • A brief report (figures, equations, key references) summarising approach and results • Any data or simulation files required to replicate the outcome If you thrive on fast feedback loops and can pivot fluidly between cutting-edge AI techniques and solid engineering reasoning, I’d love to keep you on call for an ongoing series of assignments. Note: It's industry level project and not beginner level . so avoid basic or dummy bids. if you don't have experience in R&D please don't [login to view URL]

Project ID: 40416018