You will get I will fix your Python, AI, or ML bug fast (24h delivery)
Project details
I will quickly diagnose and fix Python, ML, or AI bugs in your codebase — with clear explanations and clean, working results.
If you’re seeing errors, crashes, wrong outputs, slow inference, or models that don’t behave as expected, I follow a structured engineering process:
reproduce → isolate → fix → validate.
I’ve spent 10+ years working with production ML systems, computer vision, and Python/C++ pipelines, fixing exactly these kinds of issues under time pressure.
You’ll get:
• A working fix (not just suggestions)
• Explanation of what went wrong and why
• Clean patch / PR or updated files
• Validation that the output is correct
Typical issues I fix:
• Python errors & crashes
• ML model bugs (PyTorch / TensorFlow / NumPy)
• Wrong predictions or outputs
• Inference failures
• Performance issues
• Environment / dependency problems
• GPU / CUDA / CPU mismatches
If you want a fast, professional fix — not guesswork — this project is for you.
If you’re seeing errors, crashes, wrong outputs, slow inference, or models that don’t behave as expected, I follow a structured engineering process:
reproduce → isolate → fix → validate.
I’ve spent 10+ years working with production ML systems, computer vision, and Python/C++ pipelines, fixing exactly these kinds of issues under time pressure.
You’ll get:
• A working fix (not just suggestions)
• Explanation of what went wrong and why
• Clean patch / PR or updated files
• Validation that the output is correct
Typical issues I fix:
• Python errors & crashes
• ML model bugs (PyTorch / TensorFlow / NumPy)
• Wrong predictions or outputs
• Inference failures
• Performance issues
• Environment / dependency problems
• GPU / CUDA / CPU mismatches
If you want a fast, professional fix — not guesswork — this project is for you.
Machine Learning Tools
Kubeflow, MLflow, NLTK, NumPy, NVIDIA AI Platform, Open Neural Network Exchange, OpenCV, pandas, Python, Python Scikit-Learn, PyTorch, scikit-learn, SciPy, SQL, Stanford CoreNLP, TensorFlowWhat's included $75
These options are included with the project scope.
$75
- Delivery Time 1 day
- Number of Revisions 1
- Number of Model Variations 1
- Number of Scenarios 1
- Number of Graphs/Charts 0
- Model Validation/Testing
- Source Code
Optional add-ons
You can add these on the next page.
Additional Revision
+$25
Additional Model Variation
(+ 1 Day)
+$50
Model Validation/Testing
(+ 1 Day)
+$40Frequently asked questions
About Amin
AI/ML Engineer | Debugging, Optimization & Deployment (Python/C++)
Worthing, United Kingdom - 6:05 am local time
I help startups and teams debug, optimize, and deploy production-ready AI systems:
• Fix Python/C++ bugs, crashes, and “it works on my machine” issues
• Speed up inference (CPU/GPU), profiling & performance tuning
• Model packaging: ONNX/TFLite and deployment (Docker, APIs, cloud)
• Computer vision pipelines (detection, feature extraction, matching)
What you get when you work with me:
✅ Clear plan + fast diagnosis
✅ Clean, maintainable code (with tests where needed)
✅ Honest communication and reliable delivery
Typical engagements:
• 1–3 hours: quick bug fix / setup / error resolution
• 1–3 days: performance optimization or deployment package
Message me with your error/logs/repo link and what “done” looks like — I’ll reply with next steps.
Steps for completing your project
After purchasing the project, send requirements so Amin can start the project.
Delivery time starts when Amin receives requirements from you.
Amin works on your project following the steps below.
Revisions may occur after the delivery date.
Reproduce & isolate
I reproduce the issue locally and isolate the root cause (code, data, environment, or model).
Fix & optimize
I implement a clean fix and improve stability or performance where needed.