data engineering , Ml, Agile Methodologies, Full Stack Java, Application Resiliency, Ai, CI CD, Security, TLM automation, Automation and continuous delivery methods, AI-assisted engineering practices, Cloud native experience

Algorithms, Software Development, Debugging, data structures, Programming Languages, ML infrastructure, model evaluation, Data Processing, Optimization, model deployment, reinforcement learning

Azure ML, React, Docker, Distributed Systems, Python, Kubernetes, software engineering best practices, DL fundamentals, Go, Gradio, vector databases, classical ML, MLOps practices, GCP Vertex AI, AWS SageMaker, Streamlit

Data Science, Machine Learning, Artificial Intelligence, Python, Deep Learning, AI ML Tools, Digital Learning Technologies, Instructional Design, LMS Platforms, Curriculum Development, Technical Content Creation

Machine Learning, Data Cleaning, Exploratory Data Analysis, Tensorflow, Numpy, Pandas, Pytorch, Python, Feature Engineering, scikit-learn, Data Preprocessing, Visualization Tools, Statistical Methods

Video Processing, Tensorflow, Pytorch, Opencv, Python, ML deep learning fundamentals, IMU wearable sensor-fusion, Media Pipe, Signal Processing, scikit-learn, human activity recognition, time-series modelling, pose estimation

Retrieval-Augmented Generation (RAG), Machine Learning, SAS, Sql, Deep Learning, MLops, Excel, Python, LLM behavior control, model evaluation monitoring, LLMOps, prompt engineering, Gen AI, Agentic AI, R, Responsible AI

Kubernetes, Linux Administration, AWS services infrastructure provisioning and automation using IaC, Infrastructure monitoring observability and troubleshooting, Building and managing scalable infrastructure for ML workloads MLOps and Data Engineering platforms, GPU infrastructure management and workload optimization, AWS expertise

Orchestration, Automation Frameworks, Reliability observability security and governance controls, AI-assisted development experience, Documentation, Building systems, Designing and implementing technical solutions

data engineering , Technical Leadership, python, Pytorch, Deep Learning, Machine Learning, Numpy, MLops, Azure, retrieval-augmented generation, vector search, langchain, mentorship, model deployment, embeddings, langgraph, llmops, agentic ai, production integration, model serving, prompt engineering, pipeline architecture