Machine Learning Scientist

Machine Learning Scientist

**Enevate** Revolutionizing Electric Vehicles Technology XFC Energy Technology

Overview

*Extreme Fast Charging Technology *High Energy Density *Reduced CO2 Emissions *Low Temperature *Improved Safety

History of Batteries

*Careers *Who We Are *Li-ion Battery Pioneers *Leadership *Investors *News

Machine Learning Scientist Job ML 24-00001

Posted April 29, 2024 Apply Now

Enevate Corporation is an advanced Li-ion battery technology company located in beautiful sunny Southern California focused on developing and delivering next-gen Li-ion batteries with extreme fast charging and ultra-high energy densities using novel battery materials and architectures. With its innovative battery technologies, Enevate is focused on breaking down the barriers to mass adoption of fast-growing and clean energy Electric Vehicles (EVs).

Enevate was founded in 2005 and is well-funded by venture capital and strategic investors. As a small company, the work setting is challenging and dynamic in a tightly knit and diverse team environment that is passionate about EV technology. Enevate offers the opportunity to join in the growth stage of a startup company and contribute at all levels to make an impact. More information can be found at www.enevate.com.

We are seeking an exceptional and self-motivated machine learning scientist to join our growing R&D modeling team. Responsibilities include, but are not limited to, applying machine learning time series models, signal processing, and battery physics to develop predictive models and algorithms capable of predicting battery performance, battery state of health, and determining optimal cycling conditions.

*Cleaning and analyzing a wide variety of battery data including raw voltage curves and applying signal processing and knowledge of battery operation to develop novel data features. *Planning experiments to obtain additional data when it is required. *Communicating results with the larger R&D team and using results to make recommendations on how to improve battery performance.

Innovation is at the heart of what Enevate does, so diverse backgrounds are welcome, but familiarity with battery data is a plus.

Qualifications

**Required:** *MS or BS in computer science, engineering, physics, or chemistry with a strong background in mathematics, machine learning, and signal processing. *High proficiency with Python and machine learning packages such as Scikit-learn or TensorFlow/Keras. *Experience working with battery data. *Experience developing new data features from raw data. *Familiarity working with SQL databases. *Basic understanding of a battery's physical and chemical operating principles, including failure mechanisms. *Must be a highly motivated self-starter who is able to achieve results with minimal direction.

**Preferred:** *Ph.D. in computer science, engineering, physics, or chemistry with a strong background in mathematics, machine learning, and signal processing. *4 years machine learning experience in the battery field, particularly in the EV space. *Strong theoretical and applied background in battery physics, chemistry. *Understanding of the unique properties of Si-dominant anode systems and their relationship to cell data.

Enevate Corporation is dedicated to fostering diversity, inclusion, and promoting racial equity as an equal opportunity employer.

Apply Now - Please click on this LINK to apply to this position

***Other Positions*** *Sr. Staff Scientist Job ANO 24-00001 *Process Engineer Job ENG 24-00001 *Principal Electrolyte Scientist Job ELE 23-00004

Don't see the right opening? If you're convinced you can help us change the world, send us your info and resume whether you see an opening or not. We want to hear from you.

*Home *Revolutionizing Electric Vehicles Technology *XFC Energy Technology *Overview *Extreme Fast Charging Technology *High Energy Density *Reduced CO2 Emissions *Low Temperature Operation *Improved Safety *History of Batteries *Careers *Who We Are *Li-ion Battery Pioneers *Leadership *Investors *News

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