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Machine Learning Research Engineer

Company: Chemix, Inc.
Location: Mountain View
Posted on: November 18, 2021

Job Description:

Chemix is seeking a highly-motivated machine learning research engineer to develop and expand our AI platform for battery materials discovery. Our AI platform is the core of Chemix. Though data is first and foremost in any application of AI, it is typically very scarce in materials development. We've designed our entire R&D operation to generate battery materials datasets of unprecedented size and quality. Your mission is to leverage this data to develop the batteries that will power the electrification revolution in transportation and beyond.

As an early employee at a fast-moving startup, we expect you to quickly and creatively solve all kinds of technical problems, including those beyond your core expertise. An ideal candidate is able to learn quickly, is eager to stretch their knowledge of the ML software stack, takes pride in the quality of their work, and wants to make a real impact in energy storage technologies for electric transportation.


  • Develop machine learning models for various types of battery data and use cases
  • Maintain and extend battery data pipelines
  • Contribute code to Chemix internal codebase
  • Research and implement novel deep learning architectures, such as graph convolutional neural networks and transformers, for a variety of materials and time-series prediction tasks
  • Inform the optimization of the R&D process that generates our data


    Either 1 or 2:
    • Bachelor's degree in computer science, or the physical, chemical, or biological sciences, combined with 3+ years of work experience in use of data science for physics, chemistry, or biology
    • PhD in computer science, or the physical, chemical, or biological sciences

      As well as:
      • Extensive experience with python, pandas, numpy, scikit-learn, tensorflow/pytorch, jupyter
      • Experience with ML/software ops: git, testing, CI/CD, deployment
      • Mastery of core ML concepts: statistics, over/underfitting, model validation, uncertainty quantification, bias-variance tradeoff
      • Experience with some of the following: molecular representations and featurizations, deep learning for molecular property prediction, graph convolutional neural networks, multitask networks, generative models
      • Clear communication and good people skills
      • Strong organization and ability to manage parallel projects

        Nice to have:
        • Familiarity with data engineering tools, e.g. Airflow, Prefect
        • Experience with cloud web services (AWS, Google Cloud, Azure, etc.), Docker
        • Familiarity with high-throughput experimentation, laboratory robotics

          • Stock Option Plan
          • Health Care Plan (Medical, Dental & Vision)
          • Retirement Plan (401k)
          • Paid Time Off (Vacation, Sick & Public Holidays)
          • Family Leave (Maternity, Paternity)

Keywords: Chemix, Inc., Mountain View , Machine Learning Research Engineer, Engineering , Mountain View, California

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