Member of the Technical Staff, Computer Vision Model Training

Conquest Technologies Corporation

• $120K — $180K *
Palo Alto, CA 94303In-Person
Consumer Technology
Less than 5 years of experience
6 days ago
Job Overview by Ladders

Qualifications

  • MS/PhD/Postdoc in Physics, Applied Mathematics, Computer Science, or related field
  • Expertise in classic ML, statistics, deep learning, and Gaussian processes
  • Familiarity with transformers and self-attention mechanisms
  • Strong commitment to best practices in group coding and production environments
  • Experience with biological data is advantageous

Responsibilities

  • Develop novel methods to predict how systems respond to perturbations
  • Co-design large-scale experimental campaigns using a robotic platform
  • Utilize large structured datasets and public domain biology models
  • Manage data infrastructure from development to wet lab integration

Benefits

  • Collaborative work environment in an innovative field
  • Opportunity to engage with cutting-edge research
  • Access to large structured datasets
  • Potential for interdisciplinary work across biology and data science
Full Job Description
Responsibilities
  • Develop novel approaches and train models for prediction of perturbation-response in a complex, high-dimensional dynamical system
  • Co-design data-for-models experimental campaign at scale on robotic platform
  • Wrangle/stand up/leverage large structured data sets and foundational models for biology from public domain
  • Oversee data infrastructure across pipeline from software development environment to wet lab
Requirements
  • In office 5 days a week
  • MS/PhD/Postdoc in Physics, Applied Mathematics, Computer Science, or a related field.
  • Expertise in classic ML and statistics, deep learning, Gaussian processes, transformers+self attention
  • Zeal for best practices in group development and coding to production
  • Past experience working with biological data a plus
Tech Stack
  • Python
  • PyTorch
  • TensorFlow
  • NumPy
  • Pandas
* Ladders Estimates

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