- Help improve existing ML-based products and build new features and services using LLMs.
- Design the right inputs, retrieval strategies, and prompt structures to get the best possible output from LLMs in production (context engineering).
- Contribute to software engineering efforts, bridging the gap between ML and software engineering on the team.
- Context engineering LLM-based translation workflows — designing retrieval strategies, prompt structures, and input pipelines that maximize output quality.
- Productionizing prototypes that prove their value.
- Staying current with LLM research & tools, bringing relevant findings back to the team.
- Constructing and evaluating experiments to measure what actually works.
PythonPrompt Engineering