Machine Learning Engineer

Machine Learning EngineerA pioneering VC-backed biotech company is driving a data-driven approach to drug discovery by integrating artificial intelligence, automation, and advanced chemistry. Their proprietary platform generates massive, high-resolution datasets that fuel iterative cycles of molecular design and experimentation. This closed-loop system enables the precise mapping of molecular interactions and accelerates the development of therapeutics with unprecedented speed and accuracy. Position SummaryThe team is seeking a highly motivated and inventive machine learning engineer to join their group. In this role, you'll help build predictive models that inform molecular design decisions with exceptional clarity and reliability-powered by a scale of chemical interaction data that is unmatched in the industry. Core ResponsibilitiesBuild and refine neural architectures capable of learning from large-scale, multimodal biological and chemical datasets.Contribute to a collaborative PyTorch-based codebase by implementing modules for encoding and decoding diverse data types.Perform statistical evaluations to assess model robustness and guide improvements.Lightly curate and prepare datasets for training and validation.Integrate trained models into existing design and inference systems.Coordinate closely with fellow ML researchers to align experimental goals and share findings. Required QualificationsExperience with distributed training workflows and multi-cloud infrastructure (e.g., AWS, Docker, Redis, SQL/NoSQL).Strong proficiency in PyTorch and/or JAX for deep learning model development.Ability to manipulate and analyze data across decentralized systems.Skilled in building expressive modules for structured data generation and representation.Familiarity with molecular data structures and representations is a plus.