Senior AI Engineer

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Requirements:

• Masters, PhD, or equivalent in a computational or quantitative field (e.g., computer science, computational biology, bioinformatics, statistics, or mathematics).
• 3-10+ years of relevant work experience.
• Experience with the application of AI structured and unstructured datasets, including integration of LLMs (local and via APIs) into applications, vector databases, and integration of such tools with classical methods.
• Hands-on knowledge of modern AI frameworks, (e.g., PyTorch), including their integration into production workflows.
• Rigorous understanding of emerging and foundational machine learning methods, including deep learning (transformers, CNNs, etc.), tree-based methods, regularized regression and classification modeling, and dimensionality reduction (supervised and unsupervised).
• Industrial software engineering skills and discipline, including knowledge of at least one scripting language (e.g., Python) and database language (e.g., SQL), rigorous testing practices, and distributed tools for model training and fine tuning.

Responsibilities:

• Build systems that integrate structured and unstructured information on biological and biotech-related problems using the latest methods in AI, including LLMs.
• End to end development of AI applications, including method and model selection, fine tuning, prompt engineering, performance assessment, and collaboration with engineering teams to integrate AI into broader systems.
• Work with domain experts and data engineers to organize and curate the datasets that power these applications.
• Develop an understanding of biology, biotech investing, and drug development in the course of building these applications.