Deep Learning, Spring Boot, Natural Language Processing, Java, DevSecOps, AI ML, Github, Image Processing, Scripting, Containers, Machine Learning, Kubernetes, Apis, GitHub Actions, Google BigQuery, cloud-native platforms, CI CD, reinforcement learning, generative AI, intelligent process automation

Pyspark, Kubernetes, Docker, Python Programming, ML algorithms and statistics, Deploying ML models into production, AWS or GCP cloud

Python, Machine Learning, Deep Learning, Tensorflow, Pytorch, scikit-learn

Natural Language Processing, Deep Learning, Apache Spark, Decision Trees, Hadoop, Neural Networks, Python Programming, Clustering, Random Forest, Machine Learning Algorithms, Jenkins, Kubeflow, Airflow, Large Language Models, Boosting Algorithm, ML Flow, CI CD Pipeline, Data Munging Techniques, reinforcement learning, Bayesian Networks, Support Vector Machines

Tensorflow, Spark, Kafka, Machine Learning, MLops, Deep Learning, Pytorch, Kubernetes, Python, XGBoost, Docker, Nlp, scikit-learn, ONNX, Airflow, MLflow, AI model optimization, anomaly detection, time series forecasting, Cv, Recommendation systems, TensorFlow Serving

Python Programming, Deep Learning, Apache Spark, Statistical Analysis, Jenkins, Hadoop, Machine Learning, Airflow, Data Munging Techniques, Kubeflow, Large Language Models, ML Flow

Tensorflow, Performance Tuning, Opencv, Rest Apis, Deep Learning, Ocr, Pytorch, Machine Learning Algorithms, Google Cloud, AWS, Python, Azure, Docker, Generative AI, LLMs, feature engineering, data preprocessing, Tracking, parallelization, multimodal models, RAG, YOLO, Segmentation, ML Ops, GPU optimization, TensorRT, ONNX, distributed low-latency data pipelines, RTSP streaming video pipelines, Classification, detection, multi-object detection

containerization , Python, Kubernetes, MLops, Security best practices, Monitoring and observability, Infrastructure as Code

test automation, Tensorflow, Devops, Nltk, Pytorch, Docker, Python Programming, Keras, Kubernetes, Strong statistical quantitative skills, CI CD, Cloud experience – AWS Azure GCP, End-to-end data pipelines, spaCy, AI ML Supervised Unsupervised GenAI LLMs NLP, API design for real-time scalable applications, Linux systems, Database experience – Postgres Redshift MSSQL, Data integration across logs APIs files and databases

Hadoop, Natural Language Processing, Apache Spark, Neural Networks, Clustering, Random Forest, Deep Learning, Python Programming, Jenkins, Decision Trees, Machine Learning Algorithms, Airflow, Data Munging Techniques, ML Flow, reinforcement learning, Support Vector Machines, Boosting Algorithm, Kubeflow, CI CD Pipeline, Large Language Models, Bayesian Networks