Github, Sql, Git, MLops, Docker, Databricks, Kubernetes, Python, AWS, CI CD, Prefect, R

Machine Learning, Kafka, Sql, MLops, Docker, Spark, Python, Kubernetes, AWS, Ai, anomaly detection, Real-time data processing, Time-series forecasting

MLops, Spark, Databricks, Python, Kubernetes, AWS, rollback, deployment strategies, experiment tracking, ML infrastructure, versioning, embedding retrieval systems, classical ML models, Ray, LLM agent workflows, reproducible training data, model validation, model registry, Production Monitoring, NLP models

Docker, Kubernetes, Python, LLM inference optimization, open-source LLMs, gRPC APIs, vLLM

Machine Learning, Databricks, Sql, Python, Deep Learning, Graph Modelling, Knowledge Graphs, Identity Access Graph

model development , Data Cleaning, Sql, Numpy, Pandas, Python, offline evaluation, time-series data anomaly detection, scikit-learn, field validation, Forecasting, Classification, hybrid ML plus heuristics, Regression, rule-based systems, deployment monitoring, signal validation, drift detection, feature engineering

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

error analysis , Deduplication, Pytorch, Python, Cloud Storage, Statistical Analysis, data augmentation, model training, model-based labeling, distributed compute, Active Learning, VLMs, Hugging Face LLMs, ablation studies, dataset curation, benchmark evaluation, workflow orchestration, weak supervision, Batch Processing, inference evaluation, synthetic-data generation, Production Monitoring, data-quality measurement, diffusion models, multimodal models

Deep Learning, Nlp, Pytorch, Python, AWS, Gcp, Spark, Azure, Kubernetes, embeddings, inference, Video, end-to-end ML systems, Llm, VLM, training pipelines, fine-tuning, generative AI, cloud platforms, Vision, RAG, Production Monitoring, feature engineering, distributed data processing

classification), NLP (tokenization, Oops, C, C++, Os Fundamentals, Objective-c, Tensorflow, Pytorch, Swift, Python, language modeling, modern agentic and multi-agent systems, decoding, RAG architectures