data engineering , Database Concepts, SAS, Tableau, Qlikview, Sql, Powerbi, Selenium, Excel, Python, Pytest, GenAI, Quantitative model solutions, Automation techniques, R, Automated Testing Frameworks, Data visualization tools, Quantitative model operations

, Pytorch, Sql, Tensorflow, Hadoop, Scikit Learn, Rest Apis, MLops, Nosql, Gcp, Flask, XGBoost, AWS, FastAPI, Kubernetes, Python, Azure, Docker, Spark, Airflow, CI CD pipelines, DVC, Vertex AI, Kubeflow, MLflow, SageMaker

metrics, Apache Airflow, Logging, Cloud Infrastructure, Distributed Systems, MLops, Python, Kubernetes, Terraform, MLflow, Monitoring, Alerting, GPU Infrastructure

workflow engines , Python, tool function calling, tracing observability tooling, Logfire, AI systems in production, prompting, Temporal, OpenTelemetry, pydantic-ai, LiteLLM, MCP, agent architectures

Machine Learning, MLops, FastAPI, Python, LangChain, CrewAI, Generative AI, LLMs, AI Agents, vector databases, Claude, LangGraph, Llama, RAG, OpenAI Gemini, Prompt Engineering

Image Processing, Data Governance, Python, LLM pipelines, Deep learning neural networks, Machine learning frameworks, Chatbots, Cloud AI services, Versioning systems, Multi Cloud skills, Bias detection, Machine Learning Operations, Observability tools, Prompt management

Apis, Performance Monitoring, Version Control, Gcp, MLops, Azure, Python, Statistical Analysis, Machine Learning Algorithms, AWS, data preprocessing, cloud platforms, production-ready ML pipelines, model evaluation, deep learning techniques, feature engineering, model lifecycle management, model optimization, hyperparameter tuning