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

Python, Containerized environments, Machine Learning Engineering, Applied AI, Data pipelines, Distributed training, Model evaluation

data engineering , Numpy, Pandas, Pytorch, Python, scikit-learn, ML pipelines

Spark, Databricks, Python, LLM-based pipelines, LightGBM, Transformers, MLflow, semantic search

Java, Nosql, Machine Learning, Perl, Natural Language Processing, Big Data, Python, Document Retrieval, Map-Reduce, Search Engine Technologies

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

snowflake , Numpy, Python, BigQuery, Machine Learning, Emr, Redshift, Sql, Pandas, Aws S3, Label Studio, Airflow, data pipelines, scikit-learn, pgvector, Cpt, WhyLabs, LLM systems, OpenSearch, ICD-10-CM, Snorkel, Evidently, data-quality controls, Arize, Hcpcs, dbt, Glue

triton , data pipeline, Tensorflow, Pytorch, experiment tracking, quantisation, TensorFlow Serving, MLflow, model-serving frameworks, batching, inference optimisation, classical ML, SageMaker, LLM fine-tuning, Distillation, MLOps tooling, Kubeflow, model registries, TorchServe, feature engineering

Github, Sql, Git, MLops, Docker, Databricks, Kubernetes, Python, AWS, GenAI, GitOps governance, model versioning, lineage, CI CD, LangGraph, Production Monitoring, RAG architectures

Git, Docker, Machine Learning Algorithms, Sql, Python, Feature engineering, Model evaluation