Golang, Jax, Prometheus, Cloudwatch, Grafana, Tensorflow, Pytorch, Python, Java, Scala, MLops, Spark, Keras, Kubernetes, Scalable ML architectures, End-to-end machine learning pipelines, Automated remediation, MLflow, Prediction and drift monitoring, Model hosting, Stream processing pipelines, Big data frameworks, Model versioning, API performance monitoring, Embedding scaling, Feature stores, Data versioning

AgentOps Implementation, Python API Development, CI CD Infrastructure as Code, AI Safety Governance Compliance, GenAIOps MLOps Frameworks, Agentic Architecture Implementation, GCP AI ML Platform Proficiency, Generative AI RAG Engineering

Apache Spark, Sql, Pytorch, Docker, Databricks, Python, Model Serving Frameworks, AWS ecosystem, SHAP, scikit-learn, MLflow, TF Serving, ONNX, Cloud Platforms, LIME, Kubeflow, MLOps tools, Model Explainability tools

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

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

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

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