technical requirements , Gpu, parallel computing, AI Agents, LLMs, Computer Science, Inference Engine, vLLM, AutoGen, LangGraph, DDP, Language Models, Model Deployment, QLoRA, LlamaIndex, Prompt Engineering

Java, Scikit Learn, Hadoop Ecosystem, Kafka, Hive, XGBoost, Shell scripting, Spark, Python, Real-time data processing systems, Data ingestion transformation frameworks, ML model operationalization, Flink, Iceberg, Performance tuning on Hadoop platforms, Spark MLlib, Trino, NiFi, Cloudera Machine Learning

Power Bi, Power Automate, PowerShell, Power Platform, Microsoft Sql, Microsoft Intune, Microsoft 365, Python, Power Apps, Microsoft 365 Copilot, Jamf, Microsoft Defender

Java, Tensorflow, Pytorch, Python, GPU architecture, vLLM, TensorRT-LLM, LlamaIndex, ETL pipelines, big data processing, scikit-learn, GenAI applications, AutoGen, LangChain, LangGraph

Java, Ranger, Hadoop, Kafka, React, Hive, XGBoost, Spark, Shell scripting, Flask, Python, MLlib, Flink, Ozone, Iceberg, Trino, Nifi, Cloudera Machine Learning

MLops, FastAPI, Python, AWS, LangGraph, LangChain, Open Source LLMs, Stable Diffusion

Java, Apache Flink, Hadoop Ecosystem, Apache Spark, Apache Nifi, shell scripting, XGBoost, Apache Kafka, Python, Apache Hive, Apache Iceberg, scikit-learn, Spark MLlib

photodiodes , C, MATLAB, Solidworks, Python, LabVIEW, APDs, data collection and analysis using Excel, Lumerical FDTD, KLayout, passive waveguide photonic components, Simulation Tools, LayoutEditor, zemax, Jmp, R, receiver electronics, RSoft, mask layout tools