Transforming data into intelligent solutions.
LLM Engineer / AI Engineer with a strong focus on building production-ready Generative AI systems. Experienced in designing, developing, and deploying LLM-powered applications that integrate retrieval, reasoning, and automation to solve real-world problems at scale.
Skilled in the full AI lifecycle—from data processing and model training to LLM fine-tuning, RAG pipelines, and cloud deployment. Adept at building scalable AI services using Docker, deploying on AWS SageMaker and Vertex AI, and managing experiments and model versions with MLflow. Passionate about translating AI research into reliable, maintainable, and impactful systems.
- Build LLM-powered applications (RAG, agents, tools, workflows)
- Design and optimize retrieval systems using vector databases
- Fine-tune and evaluate Large Language Models
- Deploy scalable AI APIs and services in cloud environments
- Integrate ML systems into real-world production pipelines
- Large Language Models (LLMs)
- Transformers
- Fine-Tuning & Prompt Engineering
- Retrieval-Augmented Generation (RAG)
- Agentic Workflows
- LangChain, LangGraph, PydanticAI
- Vector Databases: Chroma, Pinecone, Qdrant
- Supervised & Unsupervised Learning
- Time-Series Analysis
- Hyperparameter Tuning
- XGBoost, K-Means Clustering
- Scikit-learn
- MLflow
- Model Deployment
- TensorFlow
- PyTorch
- Computer Vision
- Docker
- AWS SageMaker, EC2, Lambda, ECS, S3
- Vertex AI
- CI/CD, GitHub Actions
- Pandas
- Matplotlib, Seaborn, Plotly
- Tableau, Looker Studio
- MySQL, PostgreSQL
- Amazon RDS
- BigQuery
- REST API Development
- Web Scraping
- Workflow Automation (Google Sheets)
- n8n
- Technical Leadership
- Teaching & Mentorship
- Cross-functional Collaboration
- Problem-Solving
- Portfolio: https://rasyidev.pages.dev/about
- LinkedIn: https://id.linkedin.com/in/habib-abdurrasyid
- Twitter/X: https://twitter.com/rasyidevh