Nlp, Git, Typescript, Restful Apis, Python, microservices architecture, prompt engineering

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