Machine Learning Engineer

Evidium
Job Overview

logoEvidium’s mission is to scale medical knowledge and create reliable AI for the health benefit of every person.Our culture is highly collaborative and first-principles based. You’ll be joining a team developing a unique, neurosymbolic AI architecture, combining transformers, GNNs, planning / control algorithms (e.g. MCTS) and other neural and symbolic architectures. The problem we are solving is creating reliable, generalizable and knowledge grounded AI for use cases across healthcare, with a virtuous cycle of knowledge diffusion and feedback. Our early adopters are providers to enhance decision making, pharma for enhanced real-word evidence, and insurers for enhanced predictions.
ResponsibilitiesWorking as part of our team researching and engineering ML systems that can reason about medical knowledgeTraining large neural networks and machine learning systems at scale in HPC clustersArchitecting and implementing ML training, validation, and inference pipelines from idea to productResearching and implementing state of the art algorithms from literatureUsing good software engineering practices to write production-grade softwareInnovating and defining novel creative solutions to deep problems using first-principles thinking, and communicating your ideas to the teamRequirementsStrong ML background with exposure to transformers based architectures. RL, graphs/GNNs and MuZero style patterns are a plus.Proven track record in writing scalable, performant and clean python code for production and developing effective ML pipelines from initial idea to deployable productEmploymentOffice based in San FranciscoCompetitive salary and stockExcellent health benefits and a matched 401(k) planOpportunity to publish research and co-author patents

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