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Machine Learning Engineer

Engineering | New York, NY | Full Time

Job Description

Join us as we transform agriculture by democratizing data. Our global team is ‘providing data, driving progress’ - establishing the informational infrastructure necessary to increase agricultural efficiency in Africa and beyond. Our platform aggregates, deciphers and analyzes complex agricultural data while creating informative visualizations. We’re creating the tools necessary for governments, investors, banks, farmers, agricultural input providers, and others to make better decisions—decisions that can make food cheap and abundant for everyone.

Gro Intelligence is backed by venture capital and seasoned commodity investors. We are at an exciting time of hyper-growth with US headquarters in New York City and international headquarters in Nairobi, Kenya. Our global team is diverse, hardworking, ambitious—and growing! We’re looking for outstanding, collaborative, data-loving software engineers for both offices. 


We are hiring an experienced Machine Learning Engineer to join our US headquarters in New York City to:

  • Develop proprietary computational models of agricultural data, including weather, crop, trade, and pricing.

  • Establish methodology for computing large volumes of real time data.

  • Create frameworks for computing unstructured data sets that are efficient and scalable.

  • Work closely with scientists and data engineers to integrate local and sector specific factors and work closely with specialists in the field to further internal product development and external collaborations.


  • 6+ years of experience with natural language processing 

  • Strong computational skills and a deep understanding of statistics, mathematics and computer science.

  • Fluent in Python and MatLab and proficient at statistical and explicit modeling.

  • Graduate level degree in Machine Learning, Statistics, Computational Physics, Computer Science or related field

  • Ability to work collaboratively with team members across functional roles and strong communication and leadership skills.

  • Passion for enabling global food security through data driven tools.