Duration: Long Term

• Applied data science background (degree coursework, immersive bootcamp, or equivalent applied experience).
• Proven ability to design and deliver applications, with experience making practical systems design tradeoffs.
• Hands-on programming experience (Python required, plus one or more of Swift, Ruby , or JavaScript).
• Experience building and integrating applications with LLMs.
• Experience with vector databases, graph databases, or other structured retrieval approaches.
• Ability to explain and apply AI engineering practices (retrieval, context management, evaluation methods, MLOps
• patterns) to other engineers.
• Strong communication skills to translate technical findings into clear guidance.

Preferred Qualifications

• Ability to rapidly learn and apply new model capabilities and emerging AI research.
• Ability to design and execute experiments with clear hypotheses, baselines, and success criteria.
• Experience designing and running LLM evaluation pipelines that combine quantitative and qualitative methods, balance
• precision–recall tradeoffs, and align metrics with user workflows.
• Familiarity with Hugging Face ecosystem (Transformers, Datasets, evaluation libraries).
• Experience with PyTorch for fine-tuning, evaluation, and lightweight model training.
• Experience implementing a variety of model integration approaches such as LangChain and MCP .