Chemix is seeking a highly-motivated battery modeling 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 R&D operation to generate large, high-quality battery materials datasets. As a battery modeling engineer at Chemix, you'll be responsible for both the integration of physics-based battery models (DFN, ECM, thermal, etc.) into our automated experimental design pipeline at scale and the use of these models to address specific customer needs. 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 battery 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:

• Integrate physics-based battery models into our automated experimental design pipeline at scale
• Develop physics-based battery models of our commercial-format cells in python or using COMSOL to address specific customer requests
• Contribute code to Chemix's internal codebase (Python)
• Interface with our machine learning scientists, battery engineers, and customers
• Inform the optimization of the R&D process that generates our data

Requirements

• PhD in battery modeling or similar, or significant previous experience
• Extensive experience with python and standard battery modeling frameworks, e.g. PyBaMM, COMSOL
• Experience with the fundamentals of data science and software ops: git, testing, CI/CD
• Clear communication and good people skills
• Strong organization and ability to manage parallel projects

Nice to have:

• Experience with python software development best practices
• Experience with workflow orchestration tools, e.g. Airflow, Prefect, Luigi, Dagster, and scaling tools such as Dask
• Experience with machine learning and data science / statistics techniques
• Experience with cloud web services (AWS, Google Cloud, Azure, etc.), Docker, Kubernetes
• Familiarity with experimental battery 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)