Deep Learning, Git, Computer Vision, Python, real-time video streams, model optimization techniques, data preparation or processing pipelines, large-scale image and video datasets

Machine Learning, Tensorflow, Pytorch, Docker, automation, Python, AWS, Git, MLops, Gcp, Azure, Kubernetes, Airflow, Infrastructure as Code, model versioning, MLflow, Kubeflow, model registries, feature stores, DevOps practices, Scikit-learn, Ai, Monitoring, CI CD pipelines, ML model deployment

Docker, Pyspark, Pytest, Azure Databricks, Azure Cloud Services, Python, Sql, MLflow

Java, Machine Learning, Distributed Systems, Hadoop, Statistical Modelling, Sql, API Design, MLops, Spark, Python, Scalable Architectures, Large-scale Data Systems, Go, Optimisation Techniques, Scientific Computing

Spark, Java, Hadoop, Cloudformation, Yarn, Tensorflow, Hive, MLops, Docker, Sns, Python, Kubernetes, AWS, Airflow, Pipelines, H2O, EventBridge, CodeBuild, SageMaker, CodePipeline, CodeCommit, CloudTrail

AWS, Apis, integrating ML models into production systems, automated testing of model performance and stability, model evaluation techniques, feature engineering, data preprocessing, MLOps tools and frameworks

Terraform, Docker, Prometheus, Postgres, Gitlab, Grafana, Kubernetes, Python, AWS, LLMs, MLFlow

Excel, Python

Numpy, Machine Learning, Pandas, Python, MATLAB, Scikit-Learn

Pytorch, Agile, Kubernetes, Scrum