Jax, Tensorflow, Nlp, Pytorch, Python, ASR, Agentic RAG pipelines, ML lifecycle evaluation and deployment, Llm, TTS, state space models, self-learning agents, LLM orchestration, low-latency real-time ML applications

data engineering , model selection , Numpy, Pandas, Pytorch, Python, scikit-learn, ELT data pipelines, ML research methodologies, Production ML systems, ML pipelines, Hypothesis formulation and testing, Cross-validation, Performance benchmarking, Reproducible research

Pytorch, Python, C++, ROS2, reinforcement learning, ML pipelines, Robotic Systems, ML frameworks, ML concepts and evaluation methodologies, VLA models, MLOps tools and practices, anomaly detection

Java, Apis, Node.js, Kotlin, React, Gcp, Docker, Distributed Systems, Azure, Python, Kubernetes, AWS, RAG embeddings, Prompt engineering, LLMs, Vector databases, Modern frontend frameworks, semantic search, Messaging, Data pipelines, Tool calling, Event-driven architectures

Machine Learning, Python, modern ML frameworks, generative AI applications, large language models, AI technologies

C, Tensorflow, Pytorch, Javascript, data structures, Python, mathematical concepts like probability, numerical methods, object-oriented programming, custom algorithms using computer vision ML and foundational models, computer vision libraries, advanced image processing concepts, Caffe, ML architectures, linear algebra, computer vision algorithms

simulated annealing , metaheuristics , Clustering, Aws Services, Artificial Neural Networks, cloud ML solutions on AWS, mathematical optimization techniques, Airflow, workflow orchestration tools, AWS Machine Learning services, branch and bound, branch and cut, SageMaker Pipelines, machine learning techniques, genetic algorithms, decision tree learning, AWS Sagemaker, StepFunctions, Kubeflow, Gurobi, combinatorial optimization techniques, MLOps principles

Python, Machine Learning, Artificial Intelligence, REST, cloud, Tensorflow, gRPC services, MLOps tools, data pipelines