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Employment Type:Full-Time/Remote The Role: We’re seeking ahands-on AI/ML engineerto lead the architecture and implementation of our next-generation discovery pipeline. This role involves building tools that link disease biology with structure-based design, generative modeling, and safety prediction — all wrapped in a highly interoperable, graph-native infrastructure. You’ll be central to defining and building the intelligence behind our system: from data ingestion to model inference, and from semantic reasoning to compound evaluation. Key Responsibilities: Architect and implement AI-driven pipelines for multi-stage drug discovery Develop and integrate predictive modeling tools for structural and chemical analysis Work with generative algorithms to explore and optimize chemical space Connect computational models to a multi-domain biomedical knowledge graph (RDF/OWL) Design scoring and validation routines to assess novelty, fit, and biological plausibility Build scalable, containerized workflows using modern MLops and data engineering tools Collaborate with experts in biology, chemistry, and knowledge engineering to translate real-world constraints into robust, modular software Required Qualifications: Strong programming skills in Python and experience with scientific computing stacks 2+ years of hands-on experience in machine learning, deep learning, or graph-based modeling Experience building or working with biomedical or chemical data pipelines Familiarity with cheminformatics and structural biology data (e.g., proteins, small molecules) Practical experience with model evaluation, explainability, and data provenance Nice to Have: Experience with generative modeling (e.g., sequence-based, graph-based, or diffusion models) Familiarity with multi-objective optimization or reinforcement learning in scientific domains Exposure to open-source tools in bio/cheminformatics, or contributions to research software Background in systems biology, pharmacology, or drug development is a plus Why Join Us? Help build a drug discovery platform that’s explainable, reproducible, and open to the world Work at the intersection of AI, biology, and semantic data systems Join a collaborative and mission-driven team of scientists and engineers Influence not just tools, but how the future of therapeutics is discovered ·About Us: Pattern Agentix is pioneering a new model for drug discovery — open, explainable, and grounded in biological reality. We’re developing a fully modular AI platform that integrates predictive modeling, generative design, and a richly structured biomedical knowledge graph. Our goal is to build an alternative to black-box pharma pipelines, driven by transparency, biological context, and cutting-edge machine learning.