model development , Data Cleaning, Sql, Numpy, Pandas, Python, offline evaluation, time-series data anomaly detection, scikit-learn, field validation, Forecasting, Classification, hybrid ML plus heuristics, Regression, rule-based systems, deployment monitoring, signal validation, drift detection, iteration, feature engineering

S3, Sql, Lambda, Pytorch, Docker, Kubernetes, Python, AWS, OR-Tools, reinforcement learning, SageMaker, CVXPY, Gurobi

Amazon CloudWatch, Unsupervised Learning, Deep Learning, Tensorflow, Pytorch, MLops, AWS CloudFormation, AWS, Generative AI, AWS Step Functions, ML algorithms, LLMs, scikit-learn, Machine Learning Engineering, supervised learning, Amazon SageMaker, model observability, Applied Machine Learning, RAG, Amazon Bedrock, Prompt Engineering

MLops, Python, Sql, AWS Bedrock, Transformers, LLM models, AWS SageMaker

Machine Learning, data mining, Deep Learning, Tensorflow, MLops, Gcp, Pytorch, Databricks, Azure, Python, AWS, scikit-learn, data processing transformation tools, cloud environments, Optimization, big data infrastructures, CI CD for ML monitoring

Deep Learning, Databricks, Tensorflow, MLops, Machine Learning, AWS, Pytorch, data mining, Python, Azure, Gcp, cloud environments, scikit-learn, CI CD for ML monitoring, Optimization, big data infrastructures

Tensorflow, Gcp, Pytorch, Azure, Python, AWS, Generative AI, Prompt engineering, Model monitoring, LLMs, scikit-learn, Drift detection, versioning, ML ecosystems, Experiment tracking, Fine-tuning adaptation techniques

Computer Vision, Nlp, Machine Learning, Deep Learning, Representation learning, reinforcement learning, Multimodal foundation models, Large Language Models, Optimization, Generative modeling, Statistical Modeling

snowflake , Github, Cursor, Deep Learning, Tensorflow, MLops, Pytorch, Spark, Gitlab, Azure, Python, AWS, LangChain, CrewAI, LLMOps, Claude, AI Cloud architectures, Autogen, Agentic AI, Code Codex, Agentic Coding Frameworks