AWS, Pytorch, Kubernetes, Python, Tensorflow, Azure, Docker, Gcp, Scikit-learn

Python, Data pipeline automation

Apis, Microservices, Rest Apis, Python, LLM and agent evaluation frameworks, model governance, LLMs, multi-agent orchestration, agent memory design, enterprise data concepts, tool-calling capabilities, agent development frameworks, GenAI applications, observability and tracing, guardrails for AI agents, RAG architecture

Elk, Prometheus, Grafana, Nosql, Terraform, Python, AWS, Bash, Sql, Gcp, Ansible, Dynatrace, Splunk, Azure, Kubernetes, Jenkins, MLops, OpenSearch, BigPanda, Moogsoft, Open Telemetry, Harness, GitHub Actions, RAG Models, Generative AI, CI/CD pipelines, ServiceNow ITOM AIOps, PagerDuty, LLM’s

containerization , Azure ML, Distributed Systems, Etl, Arm, Kubernetes, Pyspark, Python, Docker, Terraform, Scala, Bicep, feature engineering, data architectures, infrastructure automation, ML workflows, Data Analytics tools, DevOps practices, CI CD pipelines, MLOps tooling

Machine Learning, Pyspark, Pytorch, Docker, Python, AWS, Azure DevOps, Sklearn, Automated Testing, Git, MLops, Databricks, Kubernetes, MLflow, GitHub Actions, Experiment tracking, Observability, Monitoring, Model registries, Model drift analysis, Governance, versioning, Lakehouse, CI/CD, Evidently AI

Data Science, Predictive Modeling, Eda, Python, Omics, R, Geonomics, Clinical Analysis