A persistent problem-solver who loves the process of building things - usually a combination of optimized data pipelines, scalable APIs, machine learning models.
I prefer to keep the mindset of a generalist, but I simultaneously make concerted efforts to continuously brush up on and stay updated with concepts and trends in:
- Server-side/Big-Data Engineering
- ML-Ops
I primarily work with Python-based frameworks and libraries, along with different flavors of SQL.
- ⚡ PySpark - Along with Pandas, NumPy, and other usual suspects in the world of data-wrangling and ETL-enabling APIs.
- 🌐 FastApi/Flask/Django - Experience with building APIs, but minimal use of ORMs.
- 🔥 PyTorch - For building and training machine learning models.
- 📚 MySQL / MongoDB - Working with both relational and NoSQL databases.
- ☁️ AWS Services - Experienced with:
- S3
- DynamoDB
- Lambda
- Redshift
- Glue
- ... and many many others.
- ML model deployment strategies.
- Low-latency APIs and big data.
- Distributed systems and efficient data pipelines.
- Integrating LLM-capabilties into existing workflows.