Artificial Intellience

I excell at Creating RAG based and Agentic Gen AI solutions leveraging cloud managed services (Azure OpenAI) as well as Opensource LLMs. Have a solid expertise on developing end-to-end AI solutions using frameworks like LangChain, StreamLit, LLMs (OpenAI, Gemini, LLAMA, Mistral), Embedding Models (e.g. OpenAI, HuggingFace) and Vector database Technologies (ChromaDB and FAISS).

Have extensive experience of working with multiple AI technology stacks from cloud manages services from OpenAI, Azure, AWS, Google, HuggingFace, Cohere, Meta, Anthropic, DataStacks, PineCone.

This enables me to pick and choose the right platforms as per project security, budget and performance needs.

𝐊𝐞𝐲 𝐒𝐤𝐢𝐥𝐥𝐬:

𝐂𝐥𝐨𝐮𝐝 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦 𝐚𝐧𝐝 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞:

• 𝐂𝐥𝐨𝐮𝐝 Technologies: Microservices, Kubernetes, Docker, Helm, Kafka, Rancher

• 𝐃𝐞𝐯𝐎𝐩𝐬: Git, CI/CD, Jenkins, Grafana, Prometheus, Elasticsearch

• 𝐀𝐖𝐒: IAM, EC2, S3, EBS, EFS, Secrets Manager, Cloud Trail, Cloud Watch and ELB

𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈:

• 𝐃𝐨𝐦𝐚𝐢𝐧 𝐊𝐧𝐨𝐰𝐥𝐞𝐝𝐠𝐞: Natural Language Processing (NLP), Large Language Models (LLM), RAG

• 𝐅𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤𝐬: LangChain, LangFlow, LLamaIndex, VectorDB , ChainLit, StreamLit, HuggingFace

• 𝐋𝐋𝐌𝐬: OpenAI GPT, Gemini, Titan, LLAMA, PALM, T5, Mistral

• 𝐀𝐈/𝐌𝐋 𝐬𝐮𝐢𝐭𝐬/𝐬𝐞𝐫𝐯𝐢𝐜𝐞𝐬:

o 𝑨𝑾𝑺: SageMaker, BedRock , NLP services e.g. Lex, Transcribe, Polly

o 𝑨𝒛𝒖𝒓𝒆: Azure Machine Learning Studio and AI Studio

o 𝑮𝒐𝒐𝒈𝒍𝒆: AutoML, Vertex AI, BigQuery ML

𝐂𝐨𝐫𝐞 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠:

• 𝐃𝐨𝐦𝐚𝐢𝐧 𝐊𝐧𝐨𝐰𝐥𝐞𝐝𝐠𝐞: Regression and Classification Models, Neural Networks

• 𝐏𝐲𝐭𝐡𝐨𝐧 𝐋𝐢𝐛𝐫𝐚𝐫𝐢𝐞𝐬 𝐚𝐧𝐝 𝐩𝐚𝐜𝐤𝐚𝐠𝐞𝐬:

o 𝑴𝑳 𝑷𝒂𝒄𝒌𝒂𝒈𝒆𝒔: Scikit-Learn, TensorFlow, Keras, Pytorch

o 𝑫𝒂𝒕𝒂 𝒉𝒂𝒏𝒅𝒍𝒊𝒏𝒈: Pandas, NumPy

o 𝑽𝒊𝒔𝒖𝒂𝒍𝒊𝒛𝒂𝒕𝒊𝒐𝒏: Seaborn, Matplotlib