Pyspark, Sql, Git, Docker, Terraform, Spark, Databricks, Python, AWS, CI/CD tools, MLflow, Workflow orchestration

Aws Services, Api Development, Pyspark, Redshift, Jenkins, MLops, Docker, Python, CrewAI, MLflow, AI applications, LangGraph, GitHub Actions, Glue, CI/CD, AI governance

S3, Aws Services, Api Development, Pyspark, Redshift, Jenkins, Lambda, Docker, Databricks, Python, CrewAI, ML AI applications, MLflow, CI CD, LangGraph, GitHub Actions, LLM applications, Glue

Pyspark, AWS Glue, Sql, Apache Airflow, Jenkins, Docker, Terraform, Spark, Databricks, Python, Aws S3, Step Functions, Databricks Delta Lake, MLflow, EventBridge, GitLab CI, Harness, GitHub Actions, Databricks Workflows

Tensorflow, Pytorch, Python, Java, Apis, Hadoop, Scala, MLops, Spark, Cloudera, Kubernetes, vector search, model governance, RAG embeddings, scikit-learn, MLflow, CI CD, cloud AI services, responsible AI, model evaluation, observability, LLMs, Monitoring, prompt engineering, Agentic AI, drift detection

Aws Services, Api Development, Pyspark, Jenkins, MLops, Docker, Databricks, Python, CrewAI, ML AI applications, MLflow, CI CD, LangGraph, GitHub Actions, AI governance, evaluation frameworks for AI systems

NVIDIA Collective Communications Library (NCCL), Kubernetes, Distributed Systems, infiniband, NVIDIA GPUs, Slurm, cloud computing concepts, AI ML workloads, HPC environments

Machine Learning, MLops, Apis, Containers, Python, Sql, Deep Learning, Generative AI, On-premises deployments, Ai

Apis, Distributed Systems, Python, Cloud-native architectures, AWS cloud services, Backend application development, Software engineering best practices, CI CD pipelines, AI ML application deployment