0504-001MLE

Machine Learning Engineer

Working as part of our team researching and engineering ML systems that can reason about medical knowledge.

San Francisco

Contract, C2C & W2, Full Time

Long Term

DOE

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Job Description

Posted On:

September 4, 2024

Opportunity

We are seeking a highly skilled and experienced Machine Learning Engineer. 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.

Key Responsibilities

  • Working as part of our team researching and engineering ML systems that can reason about medical knowledge.
  • Training large neural networks and machine learning systems at scale in HPC clusters.
  • Architecting and implementing ML training, validation, and inference pipelines from idea to product.
  • Researching and implementing state of the art algorithms from literature.
  • Using good software engineering practices to write production-grade software.
  • Innovating and defining novel creative solutions to deep problems using first-principles thinking, and communicating your ideas to the team.

Key Requirements

  • Strong 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 product.

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