react.js , Git, PostgreSQL, Agile Scrum, Node.js, Restful Apis, Material UI, Python, AWS

Pandas, Python, orchestration frameworks, Github Workflows, Airflow, scikit-learn, Machine Learning Operations

containerization , Databases, Java, Apis, Automated Testing, Microservices, Python, Kubernetes, orchestration technologies, Go, cloud platforms, generative AI tools, observability tooling, data engineering pipelines, stream-processing technologies

Hive, Pytorch, Spark, Keras, Python, Sql, Tensorflow, Scikit-learn, Machine Learning Techniques

Cloudformation, Jenkins, Git, MLops, Gcp, Terraform, Spark, FastAPI, Azure, Kubernetes, Python, AWS, RAG systems, MLflow, vector databases, TF Serving, statistical hypothesis testing, GitHub Actions, TorchServe, Go or Rust

Apis, MLops, Automation Frameworks, Python, Generative AI, LLMs, Cloud-Native Mastery, Bias mitigation, Explainability, Security, Azure OpenAI, Microservices architecture, AI ML Expertise, Privacy, GCP Vertex AI, AWS SageMaker, systems thinking, Conversational AI, RAG pipelines, Responsible AI, Prototype to Production

Sql, Tensorflow, Numpy, Git, Pandas, Pytorch, Opencv, Databricks, Azure, Python, data pipelines, scikit-learn, cloud platforms, MLflow, CNNs

data preparation , DataEngineer, Feature Engineering, Model Deployment, Senior Data Engineer with AI/ML, S3 Glue EMR Redshift Lambda, ? AWS SageMaker experience, ? Kafka or Kinesis for real-time streaming, ? MLOps and CI/CD for ML pipelines, ? Power BI integration with cloud-based data platforms and large-scale datasets