Agricultural Data Engineer

Mineral
Mountain View, CA
United States
Category
Remote
Job Description






OUR MISSION 


Mineral’s mission is to discover the intelligence of plantkind to feed and protect humankind. Our technology embraces the complexity of nature, unlocking agriculture data so the world can reimagine sustainable food production. This means leveraging advanced technology and use of AI across the total plant ecosystem to turn complex data into understandings that enable greater efficiency, productivity and sustainability.



The Role:


Location: US (Remote), travel to Mountain View, CA at most 1 week per month (more initially).


This is an opportunity to combine your agronomic understanding with your passion for data in ways that expand the efficiency of our MLOps pipelines. You'll be working on projects at the intersection of agriculture, big data and AI. As part of our team you will ensure we are collecting the right kinds of images, from diverse locations & times of the year, and labeling them to the appropriate standard. You'll partner with our modeling team who train, validate, and deploy perception models in production agriculture environments. You’ll have the opportunity to problem solve and be a part of the development of products that transform this space.


If you are a Data Engineer with a passion and background in weed science / agronomy, and are excited to make a difference in global food production and climate change, we’d love to talk with you.


How you will make an impact:



  • Work closely with software engineers & data scientists to ensure high quality labeled data is at hand to support machine learning and deep learning products

  • Work with cross-functional internal / external stakeholders including Data Science, Engineering and Product to support a broad spectrum of agronomy experiments

  • Develop an ambitious yet practical roadmap for collecting data that underpin breakthrough technologies in agriculture

  • Design and coordinate ground-truth data collection campaigns - from collection protocols in the field, to sample handling & evaluation in lab, to quality control of at each stage of the data pipeline for a variety of agronomic & food related projects

  • “Roll up your sleeves” and get stuff done as a member of our core MLOps Data team


What you should have:



  • BSc in agronomy, weed science, food engineering or equivalent experience

  • 5+ years of professional agricultural / food technology experience

  • Deep understanding of plant growth cycles

  • Proficiency in plant identification

  • Proficiency in Python, notebooks, & SQL for working with & interrogating large collections of labeled images

  • Strong written and verbal presentation skills

  • Demonstrated ability to self-manage, take initiative, problem-solve, and navigate through ambiguity

  • Curiosity, humility and eagerness to learn


It would be great if you also had these: 



  • Masters Degree in agronomy, weed science, food engineering, or data science

  • Experience with Databricks / Spark, or Apache Beam

  • Experience with farming and agricultural equipment

  • Experience in a startup environment

  • Startup experience, or equivalent experience on early stage software teams


The US base salary range for this full-time position is $117,500 - $180,000 + bonus + equity + benefits. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google


At Mineral, we don't just accept difference - we celebrate it, we support it, and we thrive on it for the benefit of our employees, our products and our community. We are proud to be an equal opportunity workplace and an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.


If you have a disability or special need that requires accommodation, please contact us at: mineral-accommodation-request@mineral.ai.






Employer



United States