@3x6dll9ff
MLOps & Deep Learning focus | 4 YOE in Software Engineering
Analyzed 3/21/2026
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Repos Analyzed
30
With LLM Usage
1
Total Call Sites
2
LLM Providers
1
LLM Providers
Models
---
> **"The best way to predict the future is to invent it."**
>
> I am a **Software Engineer** with **4+ years of experience** specializing in **Machine Learning Engineering**.
>
> Leveraging my background in **Electrical Engineering & CS**, I apply production-grade engineering practices to **Machine Learning** to build robust and scalable AI systems.
>
> - 🔭 **Current Focus:** Machine Learning Engineering, Deep Learning, MLOps.
> - 💡 **Mission:** To build intelligent technologies that make a tangible impact.
> - 🤝 **Connect:** Always open to discussing interesting AI/ML challenges and opportunities.
---
[](https://github.com/sponsors/3x6dll9ff)Estimate costs using published model pricing and your own volume inputs.
Model
Daily API Calls
1,000Avg Tokens per Request
1,000gpt-4o pricing
Input: $2.5/1M tokens · Output: $10/1M tokens
These estimates use published model pricing. Actual costs depend on your call volume, prompt length, and response size.