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- Bachelor’s 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.

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