Machine Learning, Information Retrieval, Distributed Systems, GPU optimization, large-scale retrieval, transformer architecture

Machine Learning, Tensorflow, Gcp, Pytorch, Docker, Azure, Kubernetes, Python, AWS, LangChain, PEFT, Generative AI, Deep Learning Architecture, Hugging Face Transformers, Fine-tuning Techniques, RAG Pipelines, OpenAI API, Vector Databases, LoRA, Cloud-native AI Architectures, Prompt Engineering

Tensorflow, Data Quality, Machine Learning, Coding, Pytorch, Version Control, Keras, Model Deployment, Model Performance Evaluation, Model Productionization

snowflake , BigQuery, Power Bi, Tableau, Data Modeling, Redshift, Sql, ELT, Python, Etl, Statistical Analysis, machine learning workflows, cohort analysis, Looker, Metabase, Segmentation, funnels, retention analysis

Tensorflow, Machine Learning, Pytorch, Artificial Intelligence, Python

Ml, Cloud Operations, Data Analytics, Incident Management, Kubernetes, cloud security, Capacity Management, Automation Frameworks, observability, technology roadmaps, risk management, Operational Excellence, Ai, Production Support, engineering standards, Disaster Recovery, Infrastructure as Code, reusable platform capabilities, Regulatory Requirements, Monitoring, business continuity, cloud adoption strategies, governance practices, Platform Engineering

Machine Learning, Python, Statistics, multimodal applications

Sql, Python, Tableau, Pyspark, Metabase, R, machine learning models, Looker

.NET, Typescript, Python, Nlp, Cloud AI services Azure OpenAI AWS Bedrock Google Vertex AI, Generative AI LLMs, CI CD technologies, API-based AI integration, Computer Vision basics, Model lifecycle training validation deployment, MLOps concepts, Monitoring alerting and observability, Object-oriented design, Machine Learning fundamentals, Deep Learning basics