AI Exploration Engineer

## Essential Duties

- Design and execute machine learning experiments to evaluate emerging AI technologies and frameworks.

- Prototype and assess end-to-end AI solutions to inform product and platform strategy.

- Formulate hypotheses and conduct structured evaluations to compare technical approaches.

- Apply modern ML engineering practices to build and test scalable, modular proof-of-concept systems.

- Contribute to the definition of best practices for experimentation, evaluation, and technical decision-making.

- Synthesize and communicate experimental results to guide investment and adoption decisions.

- Translate new research ideas and tools into functional, decision-relevant demonstrations.

- Operate independently while contributing to a highly collaborative team environment.

- Communicate technical findings clearly and concisely to both technical and non-technical audiences.

## Minimum Qualifications

- Bachelors degree in computer science, data science, information technology, statistics, economics, or a related STEM field.

- 3+ years of experience building machine learning-powered applications or tooling.

- Strong proficiency in Python and familiarity with modern ML/AI libraries (e.g., PyTorch, Hugging Face, OpenAI SDKs).

- Experience working with LLM orchestration or agent frameworks.

- Understanding of model tuning, prompt engineering, or retrieval-augmented generation (RAG) patterns.

- Experience developing and deploying applications in cloud environments (e.g., AWS, GCP, or Azure), including use of Docker and/or Kubernetes.

- Demonstrated ability to independently prototype, test, and iterate on technical ideas.

- Familiarity with ML evaluation techniques and structured experimentation workflows.

- Proficiency with version control systems, CI/CD practices, and ML observability tools.