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Machine Learning Scientist

  • Location

    San Francisco

  • Sector:

    Data Science

  • Job type:

    Permanent

  • Contact:

    Adam Oliver Brown

  • Contact email:

    adam@intelletec.com

  • Job ref:

    AOB110

  • Startdate:

    ASAP

  • Consultant:

    Adam Brown

This exciting start-up is revolutionizing novel drug discovery for psychiatric disorders through Deep Learning and ML. Founded by professors from Columbia University and UCSF and experienced technologists, they combine biotechnology, neuroscience, robotics, and machine learning techniques. They are leading the charge to help rid the world of diseases such as epilepsy, autism, and schizophrenia.

They are building a world-class high-throughput bioscience data processing platform that includes image processing, video analysis, multi-modal data integration, feature extraction, Bayesian modeling, sequence modeling, and deep learning for classification and regression. 

This role is as a core member of their machine learning team. You’ll participate in team-wide projects and lead the design and delivery of independent initiatives.

Candidates MUST have:

  • Demonstrated machine learning expertise
  • MS or PhD, or equivalent, in a quantitative field, e.g., physics, math, computer science, theoretical neuroscience
  • Python fluency; strong programming practices
  • Facility with scientific computing tools: NumPy, SciPy, TensorFlow/PyTorch, or equivalents
  • Initiative, curiosity, a bias for action, and a problem-solving attitude
  • A deep desire to learn

Added bonus points for:

  • Experience with deep learning, Bayesian modeling, computer vision, supervised and unsupervised learning techniques
  • Track record of working on challenging biological problems and manipulating biological data sets (e.g., microscopy, gene expression, genomics)
  • Familiarity with AWS
  • Experience in a fast-paced startup environment

In this position you will:

  • Design and implement data preprocessing, integration, and analysis solutions
  • Mentor and cross-train with other ML scientists through academic-style discussions
  • Collaborate with our Biology team to understand and interpret data
  • Partner with our Platform Software Engineering team to build and deploy production analysis tools
  • Work full-time hours in our San Francisco office, working closely with colleagues from many technical areas