Video Codecs, Cuda, Git, Computer Vision, Pytorch, 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

anylogic , snowflake , Tensorflow, Numpy, Pytorch, Docker, Microsoft Azure, Simio, Python, Power Bi, Sql, Pandas, Azure Data Factory, Azure Machine Learning, scikit-learn, MLflow, OR-Tools, Pulp, Gurobi, Detectron2, SimPy, Generative AI, LLMs, CPLEX, Mask R-CNN, YOLO, Azure AI Computer Vision

C, shell scripting, Python, AI model inference, accuracy-performance tradeoffs, debugging performance issues, AI deployment stacks, quantization

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

Java, Python, Hana, Postgres, Kafka, GRPC, AI ML frameworks, Go

Pyspark, Logistic Regression, Factor Analysis, Predictive Analysis, Sql, Nlp, Cluster Analysis, Python, Statistical Modelling, LLMs, Statistical tools and techniques, Multivariate Regression

Docker, Kubernetes, Python, Computer Vision, feature stores, Airflow, TFX, MLflow, ML Ops workflows, model monitoring and observability tools, cloud-native ML tools, distributed training frameworks, real-time inference systems, experiment tracking tools

triton , Pytorch, Cuda, Kubernetes, Python, Nvidia Dynamo, TensorRT

Python, Sql, Adf, Hadoop, Spark, Azure DevOps, MLFlow, Feature Stores