Sql, Tensorflow, MLops, Gcp, Pytorch, Docker, Spark, Azure, Python, Kubernetes, AWS, Observability and Monitoring, Scikit-learn, API and Microservices Architecture, Vector Databases, AI Evaluation Frameworks, Feature Stores, Reinforcement Learning concepts, Model Deployment, Agentic AI Systems, Experiment Tracking

Java, Tensorflow, Pytorch, Python, Machine Learning, scikit-learn, R, Cloud Platforms, AI Systems

Machine Learning, Amazon CloudWatch, Tensorflow, Pytorch, MLops, AWS CloudFormation, AWS, Generative AI, AWS Step Functions, scikit-learn, Model Observability, Amazon SageMaker, Amazon Bedrock

triton , Pytorch, FastAPI, Kubernetes, Python, Docker, Restful Apis, Sagemaker, ML technologies, document databases, TensorRT

Video Codecs, Cuda, Git, Pytorch, Computer Vision, Python, Weights Biases, PEFT, model evaluation frameworks, video processing pipelines, attention mechanisms, GPU-based training, deep learning frameworks, MLflow, CNNs, streaming technologies, inference optimization, LoRA, continuous experimentation infrastructure, Transformers, MLOps tools

snowflake , Spark, Sql, Databricks, Kafka, Machine Learning, MLops, Data Science, Python, LLMs, Airflow, Probabilistic modeling, Tree-based models, Feature engineering, Generative AI, Transformers

Pytorch, Azure, Aws

Python, Data Science, Automated scoring pipelines, ML engineering, LLM evaluation