Machine Learning, Deep Learning, Tensorflow, Pytorch, Opencv, Python, Computer Vision, GenAI, Prompting, LLMs, GenAI systems, OCR engines, PIL, Fine-tuning

data engineering , Numpy, Pandas, Pytorch, Python, Testing and release, scikit-learn, Development processes, ELT data pipelines, ML research methodologies, Build processes, Production ML systems, Source control management, ML pipelines

Java, Docker, Kubernetes, Python, TFX, AWS SageMaker, Kubeflow, Google Vertex AI, Go, MLflow, Metaflow

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

Sql, Devops, Rest API Development, Cloud, FastAPI, Python, Model Context Protocol, Knowledge Management, PromptFlow, MLflow, Agentic AI LLM Platforms, AI Evaluation Frameworks, RAG, MCP

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

Machine Learning, Sql, Spark, Python, Neural architectures, ML libraries, Regression, Gradient-boosted trees, ranking, Classification, Causal reasoning, Evaluation frameworks

Tensorflow, Pytorch, Python

containerization , MLops, Distributed Systems, Logging, LLM-based systems, Alerting, Model observability, Vector databases, Drift detection, Scalable inference systems, Machine Learning Engineering, Orchestration patterns, Model training, Cloud-native architectures, Embeddings, Data ingestion, Experiment tracking, cost tracking, ML platform development, tracing, Feature management, Model registry, Monitoring