data engineering , Machine Learning, Apache Spark, Kubernetes, Airflow, Apache Iceberg, Frontier AI models, ML Platform Development, Ray, NVIDIA Workbench, Flink, SageMaker, Jupyter Notebooks, Kubeflow, Vertex AI, MLFlow

Rust, Storm, Cassandra, Cloudformation, Kafka, Dataproc, Devops, Gcp, shell scripting, Terraform, Elasticsearch, Spark, Amazon Rds, Python, AWS, Infrastructure as Code, AWS EMR, ElastiCache, Go, Flink, Cloud SQL, Site Reliability Engineering

tokenization , Machine Learning, Git, Docker, Rest Apis, Python, AWS, embeddings, vector databases, Anthropic, prompt engineering, LLM APIs, AI-assisted development tools, GenAI ecosystem, OpenAI, RAG architectures

data engineering , Predictive Analytics, Distributed Systems, MLops, Cloud-native architecture, Analytics engines, Telemetry-driven insights, Cloud platforms, Model serving and inference platforms, Generative AI, AI systems engineering, High-throughput data pipelines

Ml, Java, Aws Cloud, Kubernetes, Python, Generative AI, open-source frameworks, Ai, AI agent frameworks, High Performance distributed architecture

snowflake , BigQuery, Dynamodb, Emr, Redshift, Aerospike, Spark, AWS, Airflow, Real-Time vs Batch Data Processing, Cleanroom, cloud data architectures, Data Table Format, Iceberg, Hudi, Scylla, Data Lakehouse, Delta, batch real-time data processing systems, High throughput distributed system APIs, Zero-Copy Data Sharing