Machine Learning Research Engineer Internship

Sunnyvale, California, United States

Applications have closed

Chemix is seeking a highly-motivated machine learning research engineer intern to help develop and expand our internal AI capabilities 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. As a machine learning research engineer intern at Chemix, your mission is to work with our machine learning scientists to (i) suggest, prototype, and test new algorithms, and (ii) design and build the machine learning pipelines that turn our data into actionable results. You'll make a fundamental contribution to developing 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 and data software stack, takes pride in the quality of their work, and wants to make a real impact in energy storage technologies for electric transportation.

Responsibilities:

  • Suggest, prototype, and test new ML algorithms based on our large materials datasets
  • Discover and introduce new ML models, statistical methods, software frameworks, and libraries
  • Contribute code to Chemix's internal codebase (Python)
  • Interface with our data scientists, data/software engineers, and battery engineers
  • Implement best practices for code development and ML-ops, experiment tracking, etc
  • Inform the optimization of the R&D process that generates our data

Requirements

  • In-progress, or recently completed, MS or PhD in applied machine learning or adjacent field.
  • Experience with core data science, machine learning, and statistics concepts
  • Experience with the python data ML stack: pandas, numpy, sklearn, pytorch / tensorflow
  • Experience with the fundamentals of ML and software ops: git, testing, CI/CD, experiment tracking, cloud computing
  • Clear communication and good people skills
  • Strong organization and ability to manage parallel projects

Nice to have:

  • Previous battery data experience
  • Familiarity with experimental chemistry/materials science

Benefits

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

Tags: Chemistry CI/CD Git Machine Learning ML models NumPy Pandas PhD Pipelines Python PyTorch R R&D Research Scikit-learn Statistics TensorFlow Testing

Perks/benefits: 401(k) matching Career development Equity Health care Medical leave Parental leave Startup environment

Region: North America
Country: United States
Job stats:  127  56  1

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