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

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

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

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

Vertex AI (Google), Pytorch, Boost, Python, Gcp, Tensorflow, Devops, Prometheus, Terraform, Spark, Sci-Kit Learn, LangChain Development, Gemini

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

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

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

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

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