Hello, I'm Bandhvai sakhmauri 👋

I'm a Devops Engineer with expertise in Machine Learning, NLP, Generative AI, and Large Language Models. working in DevOps and being a skilled Site Reliability Engineer with good hands-on experience supporting, automating, and optimizing mission critical deployments in AWS, leveraging configuration management, continuous deployments, and DevOps processes. Making my way into Machine learning and MlOps by training with AWS sagemaker and Bedrock services, deploying ML models on EKS ( kubernetes)

About Me 🤖

My journey into Machine leatning and AI has been fueled by curiosity, problem-solving, and a drive to transform data into meaningful insights. With a strong foundation in Devops SRE MlOps, I have worked on ML engineering, ML deployments, scaling models, Training and inference optimizations

I'm currently working on end-to-end ML pipelines, optimized models for business applications, and worked on LLMs, pytorch, and AI-driven recommender systems, automatic speech recognition, sentimental analysis, object detection and computer vision.

I specialize in Machine Learning (Supervised, Unsupervised, XGBoost, Random Forest), NLP (Transformers, RAG, Prompt Engineering), Deep Learning (CNNs, RNNs, LSTMs), and Large Language Models (OpenAI, Gemini, Hugging Face, LangChain). My skill set includes Python, MongoDB, TensorFlow, PyTorch, and Cloud (AWS, GCP, Azure).

I am passionate about applying AI to solve real-world problems, optimizing predictive models, and enhancing explainability in ML systems. I thrive on building scalable AI solutions, optimizing trianing and inference speeds, Hybrid cloud AI deployments, integrting AI features in exsiting Saas application, evaluating and experiment tracking of LLM's, improving LLM consistency, and integrating cutting-edge AI techniques into business strategies.

Let’s connect! I’m always open to collaborations, discussions, and innovative AI-driven projects. Check out my GitHub for my latest work, or reach out via LinkedIn or via email [email protected].

Key Areas of Expertise:

Statistical Programming Language: Python Numpy Pandas SciPy, R
Machine Learning and Deep Learning Frameworks: Scikit-Learn PyTorch Tensorflow
Cloud and Databases: AWS, Azure, GCP
Data Visualization Tools: Matplotlib Seaborn Tableau PowerBI Looker Google Analytics
AI Prowess: Large Language Models (LLMs) Retrieval Augmented Systems (RAGs) Fine-Tuning Generative AI Agentic AI Transformers LangChain GPTs HuggingFace Gemini Llama WhisperAI BERT RoBERTa BART LangGraph Groq OpenAI Diffusion Models GANs CGANs StyleGANs
Machine Learning: Supervised Learning Unsupervised Learning Regression Classification Random Forest XGBoost Ensemble Learning
Natural Language Processing (NLP): NLTK SpaCy Embedding Models
Deep Learning: ANNs CNNs RNNs LSTMs GRUs
Model Development: TensorFlow, PyTorch, Hugging Face
Data Engineering & ETL: Apache Airflow, Prefect, Kafka
MLOps: Kubeflow, MLflow, ZenML
CI/CD: Github Actions, Jenkins,Teamcity, CircleCI
Cloud AI Deployment: AWS SageMaker, AWS bedrock
Edge AI & Hybrid Deployments: NVIDIA Jetson,
LLM & RAG Implementation: LangChain, Pinecone, Weaviate, chromaDB
Observability & Monitoring: Prometheus, Grafana, Datadog