Short-Term Trainer
2 weeks ago
About the Role:
I'm looking for a
hands-on trainer or developer
who can provide
short-term, focused training (2–4 weeks)
in
GPU programming using Python
. The goal is to build a strong conceptual and practical foundation — enough to apply GPU acceleration in academic and research projects.
If you're an experienced Python developer with CUDA, Numba, or PyTorch GPU optimization experience, and you enjoy teaching, this is a great short-term engagement.
Key Topics / Learning Goals:
- GPU architecture basics (threads, blocks, warps, memory types)
- Writing and running CUDA kernels using Python
- GPU acceleration using
Numba
,
CuPy
, and/or
PyTorch Tensor operations - Profiling and optimizing GPU code
- Hands-on mini projects (e.g., matrix multiplication, image filters, ML model acceleration)
Requirements:
- Strong knowledge of
GPU computing
and
Python-based parallelism - Experience with at least one of:
- NVIDIA CUDA Toolkit
- Numba / CuPy
- PyTorch / TensorFlow GPU workflows
- Prior teaching or mentoring experience preferred (not mandatory)
- Ability to conduct
live online sessions
(flexible hours, 1–2 hrs/day preferred)
Engagement Details:
- Duration: 2–4 weeks (flexible, part-time)
- Mode: 100% Remote
- Schedule: Flexible (evenings or weekends possible)
- Compensation: Open / based on experience
Ideal For:
- GPU developers who enjoy mentoring
- AI/ML engineers familiar with performance optimization
- Educators or freelancers with experience teaching technical courses
How to Apply:
Please comment or DM with:
- Your experience with GPU programming in Python
- Tools/libraries you use (CUDA, CuPy, Numba, PyTorch, etc.)
- Expected hourly rate or total fee
- Availability (start date and preferred time slot)
-
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