Algorithms, Computer Vision, Debugging, data structures, Python, ML infrastructure, LLMs, Data Processing, GenAI techniques, model deployment, language modeling, model evaluation, Optimization, Multi-Modal Large Vision Models

.NET, Machine Learning, Amazon S3, ELT, Python, AWS, Java, Artificial Intelligence, Apache Spark, Sql, Devops, Spark, Databricks, Rest Apis, Etl, Apache Iceberg, Airflow, Infrastructure as Code, Pinecone, Vector Search, Chroma, semantic search, Generative AI, Agentic AI, dbt, Delta Lake, Milvus

Python, Rest Apis, AWS, MongoDB, LLM integration

Java, Machine Learning, Kafka, Tensorflow, Hive, Pytorch, Spark, Kubernetes, Python, Airflow, Ray, Kubeflow

AWS, Java, Python, Cloud Infrastructure, multimodal AI pipelines, LLMs, RAG-based systems, GenAI systems, AI ML systems, Go, vector databases, embeddings

Deep Learning, Numpy, Pytorch, Opencv, Python, Seaborn, Computer Vision, Matplotlib, scikit-image, LSTM, PIL

Java, Graphql, Scala, Kafka, TigerGraph, MLops, Docker, Neo4j, XGBoost, Spark, Kubernetes, Python, AWS, Airflow, pgvector, Qdrant, LightGBM, Go, MLflow, Flink, Neptune, Kubeflow, Milvus

Data Quality, Microservices, Automated Testing, release management, Python, Apis, Git, Rest Services, Data Transformation, non-relational databases, Azure services, data pipeline development, Generative AI technologies, Relational Databases, AI Agents, MLOps practices, DevOps practices, enterprise integrations, Copilot technologies