Python, Llama.cpp, Ollama, AI frameworks

Machine Learning, Unsupervised Learning, Python, agentic AI, adversarial machine learning, reverse engineering model behaviors, debugging complex ML failure modes, supervised learning, generative models, investigating emerging technical threats, reinforcement learning, evaluating frontier AI systems, data poisoning, ML safety, prompt injection, ML interpretability, designing robust proactive defense mechanisms, multi-object optimization, adversarial robustness, model backdoor detection, adversarial machine learning AI agent security, red-teaming frontier AI systems

snowflake , containerization , Pyspark, AWS Glue, Kafka, Numpy, Python, AWS, Java, Scala, Devops, Pandas, MLops, Gcp, Matplotlib, Spark, Apache Beam, Azure, data pipelines, Flink, Data Proc, Azure DataFactory, analytics libraries, cloud platforms, distributed computing frameworks, DataOps, GCS

Pyspark, Apache Spark, Kafka, Sql, Pytorch, Databricks, Ocr, Python, LangChain, PEFT, PyMuPDF, LLM prompting, Text-to-Speech models, MSAL, LoRA, Delta Lake, VLM, Microsoft Fabric, LlamaIndex

Algorithms, data structures, Python, planning memory modules, retrieval graph algorithms, prompt engineering, Agent framework development, LLM fundamentals, RAG optimization, SFT for LLMs, fine-tuning workflows, RLHF

Python, Tensorflow, GPT3, APIs for interacting with LLMs, Lang Chain, AgentGPT, Flowise, LlamaIndex

Git, Aws Redshift, Tableau, Python, Sql, Metabase, R, n8n, Streamlit

Java, Servicenow, Vue, PostgreSQL, Prometheus, Node.js, Grafana, Jira, Nosql, Git, Docker, MySQL, Kubernetes, Python, LangChain, Go, Autogen, Next.js, LlamaIndex

Typescript, Javascript, Python, AI-enabled tools, RAG systems, copilots, AI agents, automation workflows, LLM apps