AI/ML Engineer who enjoys designing and deploying end-to-end AI systems including LLM document pipelines, multi-agent orchestration frameworks. I also have 2 papers published in IEEE and Springer.
I enjoy designing thoughtful architectures, working with distributed systems, and turning complex ideas into production-ready solutions.
- Data Engineering & Pipelines
- Machine Learning & Applied AI
- Cloud-Native Architecture (AWS)
- System Design & Scalability
- Backend & Distributed Systems
Languages:
Python, Java, SQL
Cloud, DevOps & Frontend:
Docker, React.js, Node.js, HTML5, CSS3, jQuery
Cloud & Infrastructure:
AWS (Lambda, API Gateway, S3, DynamoDB, Cognito, ECR), Docker
AI, Data & ML:
NLP(Text Classification, TF-IDF, Word Embeddings (Word2Vec), Similarity Search), Supervised & Unsupervised Learning, Feature Engineering, Model Evaluation, Prompt Engineering & Structured Output Enforcement (LLMs), RAG, Langchain, Langraph
DevOps & Tools:
Git, CI/CD, Linux
Frameworks / Libraries: TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy, PySpark, Apache Spark
- Building serverless microservices on AWS
- Exploring scalable system design patterns
- Applying machine learning to real-world problems
- Strengthening cloud-native development practices
- LinkedIn: https://www.linkedin.com/in/aryakinagi/
- GitHub: https://github.com/Aryakinagi4
Know more about me here - https://arya-kinagi-2sv7lkl.gamma.site/
⭐ I’m always open to collaborating on meaningful engineering problems and learning new technologies ⭐