AI/ML Engineer

$130,900 - $177,100/Yr

GlaxoSmithKline - Cambridge, MA

posted about 1 month ago

Full-time - Mid Level
Cambridge, MA
Chemical Manufacturing

About the position

The AI/ML Engineer position at GSK involves developing and validating advanced machine learning models to address complex scientific challenges in healthcare. The role focuses on applying cutting-edge AI methodologies to analyze multi-modal high-content data, contributing to the development of novel therapies and personalized drugs. Engineers will work collaboratively within cross-disciplinary teams to generate actionable insights that impact various stages of drug development.

Responsibilities

  • Carry out product-driven research on novel machine learning methods to analyze terabytes of internal multi-modal high-content data.
  • Design approaches to deconvolve real biological signals from confounding effects inherent in high-throughput biological data.
  • Leverage internal high performance computing cluster and cloud compute to train and productionize models at scale.
  • Work closely with domain experts on cross-disciplinary teams to generate actionable insights that impact target identification, hit identification, and safety testing.
  • Contribute to the developing codebase with well-tested, production-ready code.

Requirements

  • Graduate studies in computer science, engineering, applied mathematics, machine learning, or equivalent practical experience.
  • 2+ years of experience in machine learning and software engineering best practices.
  • 2+ years of experience working in a collaborative CI/CD software development environment, including use of git.
  • 2+ years of experience developing, implementing, and training deep learning models with PyTorch, Tensorflow, or other deep learning frameworks.

Nice-to-haves

  • Experience working with high-content imaging and diverse multi-omics.
  • Knowledge in disease biology, molecular biology, and biochemistry.
  • Track record of writing software in a team in industrial environments or open-source projects.
  • Track record of projects or peer-reviewed publications at the intersection of machine learning and life sciences.
  • Mentality of commit early and often, metrics before models, and shipping high quality production code.

Benefits

  • Health care and other insurance benefits (for employee and family)
  • Retirement benefits
  • Paid holidays
  • Vacation
  • Paid caregiver/parental and medical leave
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