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

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

Tensorflow, Machine Learning, Pytorch, MLops, Natural Language Processing, Python, Sql, Deep Learning, Vector Databases, Generative AI, Retrieval-Augmented Generation

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

Natural Language Processing, Deep Learning, Python, Scala, Machine Learning, Search Technologies, Retrieval Augmented Generation, Large Language Models, reinforcement learning, Go, Embeddings

Machine Learning, data mining, Deep Learning, Tensorflow, MLops, Gcp, Pytorch, Databricks, Azure, Python, AWS, scikit-learn, data processing transformation tools, cloud environments, Optimization, big data infrastructures, CI CD for ML monitoring

containerization , Github, Unit Testing, Tensorflow, Numpy, Docker, Python, Scipy, Pandas, Kubernetes, Workflows, Databricks, CI CD Pipelines, scikit-learn, Cluster Creation, Edge Deployment, Azure Cloud Architecture for ML, ACR, Repo Management, Portainer, ML Model Design, Deployment

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