Tensorflow, Pytorch, Python, MLops, Spark, Databricks, GPU infrastructure, model versioning, event tokenization, efficient attention, attention-based architectures, positional embeddings, mixed-precision training, self-supervised pretraining, gradient accumulation, automated retraining, experiment tracking, masked modeling, deep learning models, distributed strategies, contrastive learning, check-pointing, downstream fine-tuning, Production Monitoring

Tensorflow, Nlp, Jax, Pytorch, Python, ASR, TTS, Llm

Python, ML tooling, Llm

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

Git, Pytorch, Docker, Linux, FastAPI, Python, Computer Vision, Deep Learning, Transformers, Hugging Face, GPU training workflows

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

Deep Learning, Git, Computer Vision, Python, real-time video streams, model optimization techniques, data preparation or processing pipelines, large-scale image and video datasets

Machine Learning, Personalization, Sql, Spark, Databricks, Rest Apis, Python, MLops, AWS Cloud platforms, Microservice-based model serving, Data Processing, collaborative filtering, Feature engineering, Recommendation Systems, Model training and evaluation, Ranking algorithms, ML pipelines, Batch inference, Hybrid recommendation systems

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