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Location: San Francisco, US

YOU

A machine learning professional with wide-ranging experience training and shipping advanced neural networks. A skilled programmer and data modeler with knowledge of varied ML approaches and environments. You are motivated to utilize your skill set in a scientific workplace and to see the fruits of your labor make an impact through patient-centric biotechnology. If this is you, please read on.

US

We are tapping into a new level of biological understanding. Glycoproteomics is the language that InterVenn is translating for the benefit of patients, researchers, and human health. Our diverse backgrounds and experiences have culminated in a unique startup working at the intersection of mass spectrometry, glycobiology, and AI to develop precision medicine products. If this sounds like a good fit, please read on.

THE DETAILS

We are seeking a sharp individual familiar with the cutting edge of machine learning to join as an AI Engineer. The optimal candidate will have experience building and testing neural networks in enterprise or research settings. The ability to learn advanced scientific concepts and contribute in a fast-paced lab environment is crucial. The candidate will work closely with the R&D team on a variety of projects, developing AI products to supercharge mass spectrometry workflows. For this employee, simply building ML products is not enough Рthey want to positively impact the greater research and healthcare communities. 

RESPONSIBILITIES

  • Develop new machine learning systems for processing mass spectrometry data, and expand existing implementations
  • Interface with R&D to augment and supercede manual processing in mass spec workflows
  • Apply skills in bioinformatic analysis to large proteomic datasets
  • Program in Python and assess data pipelines for general scientific use
  • Work closely with the software development team to turn AI models into usable software
  • Keep up-to-date with deep learning techniques as applied to mass spectrometry and biology
  • Distill complicated ML insights into reports for presentation to the greater company

QUALIFICATIONS

  • Ph.D. in a quantitative field such as Computer Science, Mathematics, Statistics, or Bioinformatics, with 0-3 years experience developing deep learning systems in industry or academia
  • Alternatively, an MS in a similar quantitative field with 3+ years relevant experience¬†
  • Extensive experience in the Python programming language, utilizing ML environments such as Pytorch and Tensorflow
  • Familiarity with cloud computing environments such as Google Cloud and AWS
  • Preference will be given to candidates with experience analyzing mass spectrometry data or demonstrated expertise in scientific research
  • Familiarity with shell scripting, the Linux operating system, R programming, or Github will also be useful
  • Ability to come up to speed quickly and seek out new solutions independently
  • A genuine desire to impact patient lives and contribute to the greater scientific community
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