data preparation , Python, Apis, Agentic systems, Quality Monitoring, Model deployment, Deployment, Infrastructure for serving ML/LLM systems, Human-eval workflows, LangGraph, AI ML pipelines, Sovereign LLMs, LLM evaluation systems, Data pipelines, Backend systems, Regression tests, Tool calling, Monitoring, LangChain, SFT, Cloud platforms, Benchmarks, Multi-step reasoning pipelines, Services, LoRA, QLoRA

Machine Learning, Jax, Scipy, Numpy, Pytorch, Python, Hugging Face Transformers, llama.cpp, SGLang, vLLM, Coding Agents, Command-line tools, Hugging Face Tokenizers

probability , Tensorflow, Pytorch, Spark, Sql, Python, Data Analysis, Statistics, Scikit-Learn

Jax, Tensorflow, Pytorch, Python, Stable Baselines3, MuJoCo, DQN, Ray RLlib, CleanRL, Gymnasium, ppo, actor-critic methods, SAC, reward shaping

Machine Learning, Pytorch, Python, Deep Learning, Speech Recognition, Signal Processing

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

Python, Logging, Together, Model observability, Multi-model architectures, LLM integration, Model routing, Model cascades, Anthropic, Groq, Ensembles, LLM APIs, Inference platforms, Automated evaluation pipelines, Fallback mechanisms, Production Monitoring, Error handling, OpenAI, Prompt design, Model evaluation, Monitoring

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