AI/ML Platform Architect

Brief DescriptionJob Description

Help architect, design and implement ThinkBio.Ai AI insight and data platforms; design agentic architecture for the AI platform Evaluate and analyze foundation models for protein structure, clinical data, genomic data and small molecule data; fine tune foundation models. Design loss functions relevant to biological applications Design scalable data models for multi-modal biological data Create a componentized architecture with component level structured APIs Design and implement knowledge graphs for biological data; apply deep learning based methods to create representations from knowledge graphs Work closely with other team members and partners to identify most critical data centered challenges and address them using cutting-edge computational, statistical and machine learning applications

Preferred SkillsRequirements

Ph.D. in Computer science, AI/ML, Mathematics/Statistics 10+ years’ experience and technical expertise in AI platforms, data platforms, deep learning models

Solid understanding of computer science fundamentals

data structures: trees, directed and undirected graphs, hash tables, heaps algorithms: search, sort, rank, graph based algorithms

Solid understanding of statistical/mathematical concepts

probability theory correlation metrics Bayesian probability Statistical regression methods

Good understanding of GPU architectures – CUDA Proficiency in Python, C, C++ Expertise in AI frameworks: PyTorch, TensorFlow Exposure to agentic frameworks like LangChain and LlamaIndex Firm grasp of modern statistical methods and machine learning techniques, and their applications to large-scale, data Ability to manage projects with minimal supervision, using creative and analytical thinking. Ability to drive highly collaborative work across the organization and outside the company Excellent oral and written communication skills

Preferred Skills  

Experience and understanding of how bioinformatics and data science can best be applied to speed up drug discovery Basic understanding of biological concepts and a familiarity with drug development process Knowledge of bioinformatic tools and databases to analyze genomics and proteomics data.