Experience: 3+ years applied machine learning, with hands-on focus on NLP, transformers, or generative AI systems.
LLM and Agent Tools: Hands-on experience with LLM-related libraries (e.g. LangChain, LlamaIndex, OpenAI API, CrewAI, or similar) and services (Azure Prompt flow, AWS Bedrock agents, or similar)
Agentic Systems: Experience designing multi-step agents that combine LLM reasoning with tool/API calls, with safeguards against errors, loops, and unsafe tool use.
ML Foundations: Proven experience building and deploying machine learning models to production (API, batch, or streaming).
Coding: Fluency in Python, with clean, modular, production-grade code practices.
Experimentation: Strong ability to design and analyze ML experiments; track performance using metrics, not gut feel.
Deployment: Ability to develop, deploy and monitor AI-powered applications in cloud environments (e.g. AWS, Azure, GCP) using APIs, batch, or streaming architectures. Familiarity with containerization, versioning, and CI/CD.
Responsible AI: Experience implementing privacy, bias mitigation, safety guardrails, or related practices.