Machine Learning, Numpy, Nlp, Pytorch, Elasticsearch, XGBoost, Python, AWS, Spark SQL, Recommender Systems, Apache Spark, Azure ML, Pandas, Gcp, Airflow, scikit-learn, Statistical Models, Vector Databases, Deep Learning Frameworks, Kubeflow, Spark ML, MLFlow, Algorithms for Search Retrieval, MLlib, ML Orchestration Tools

Pyspark, Sql, Rest Api, Bash Scripting, MLops, Gcp, Docker, Linux, Databricks, Azure, Kubernetes, Python, AWS, Azure DevOps, MLflow, GitHub Actions, Kubeflow

Machine Learning, Databricks, Sql, Python, Deep Learning, Graph Modelling, Knowledge Graphs, Identity Access Graph

Machine Learning, Pyspark, Dynamodb, Apache Spark, Sql, Redis, Git, Docker, Terraform, AWS ECS, Apache Kafka, Flask, Databricks, FastAPI, Python, AWS

Elk, Prometheus, Grafana, Azure ML, MLops, Docker, Python, Kubernetes, monitoring and observability, production ML systems, CI CD pipelines, Vertex AI, Linux systems, cloud ML platforms

snowflake , Github, Cursor, Code, Deep Learning, Tensorflow, Pytorch, MLops, Spark, Gitlab, Azure, Python, AWS, CrewAI, LangChain, LLMOps, Codex, Claude, AI Cloud architectures, Autogen, Agentic AI, Agentic Coding Frameworks

bagging , data mining, Nlp, Elasticsearch, Python, Java, Machine Learning, Hadoop, Information Retrieval, Emr, Pig, Hive, Spark, Computer Vision, Statistical Techniques, machine translation, algorithms and data structures, Deep Neural Networks, numerical optimization, large language models, high-performance computing, large scale distributed systems, parallel and distributed computing, Classification models using Boosting

Yaml, FastAPI, Python, Docker, Ansible, Json, Git, Kafka, infrastructure-as-code, NVIDIA Triton Inference Server

Spark Streaming, Kinesis, MLops, Aws Services, Pyspark, Kafka, Databricks, Sql, ELT, Etl, Airflow

Scipy, Java, Machine Learning, Hadoop, Tensorflow, Numpy, Python, scikit-learn, MxNet, neural deep learning methods, Analytical Techniques, R, Spark MLLib