ML Data Scientist

We are a climate tech company committed to reversing climate change. How do we reach this lofty goal? By disrupting the agriculture industry! Founded by globally recognized innovators in science and ag technology, Regrow is unlocking the power and profitability of resilient agriculture across the supply chain — from growers to global food brands. Regrow combines best-in-class agronomy, soil and carbon modeling, and innovative data collection to deliver customized, site-specific, and scalable solutions to the agri-food industry. Our customers are frontrunners in agri-food and agtech, ranging from global market operators, project developers, global food brands, and independent farmers. We help partners measure their impact on the environment, model and implement changes that will be environmentally and financially sustainable, and track partners’ progress against sustainability goals. We're backed by leading investors, such as Galvanize Climate Solutions, Microsoft's Venture Fund, Cargill, The Grantham Environmental Trust (NCO), TIME Ventures, Main Sequence Ventures (MSEQ), and more, all of whom believe in our vision to change the world through resilient agriculture.
Our Mission: Agriculture has the power to reverse climate change. We believe science and technology can help us get there. Our goal is to use farmland to cool the earth. We are currently monitoring 200 million acres of land in over 45 countries. This year alone, with just one project, our carbon emissions reductions are equivalent to taking 17,000 cars off the road! We are already on our way to a more sustainable planet.
Growth You’ll Foster: As an ML Data Scientist at Regrow, you will create the data products behind our agricultural monitoring, reporting, and verification tools. Using your expertise in deep learning model development, you will build the tools Regrow uses to identify regenerative agricultural practices globally, allowing growers and the companies that depend on them to build more sustainable supply chains. 

What you will do:

• Design, implement, and deploy Deep Learning and Machine Learning models for imagery time series analysis, classification, and segmentation.
• Applications are focused on agriculture, rangeland management, and land cover/land use mapping.
• Identify and integrate relevant remote sensing and other spatial datasets for model development and improvement, including multispectral and SAR satellite imagery, weather and soil data, in-field measurements, and farm machinery datasets.
• Leverage familiarity with current best practices in remote sensing science and machine learning to drive innovation across the Data Science organization.
• Provide domain expertise to cross-functional discussions about product design, improvement, and implementation.
• Advocate for practical, relevant, and scientifically valid solutions.
• Contribute across the full product life-cycle: conduct R&D on potential focus areas, develop proof of concept data products for new offerings, and iterate on existing models to improve core products. 

Qualifications:

• Advanced degree or equivalent experience in Earth Science, Remote Sensing, Computer Science, Statistics, Artificial Intelligence, or a related field.
• Experience building statistical and machine learning models using remote sensing datasets. Familiarity with deep learning approaches (e.g. transformers) and experience using deep learning frameworks such as PyTorch, Keras, or TensorFlow.
• Strong Python programming skills, including scientific and machine learning libraries (NumPy, SciPy, SKLearn, TensorFlow, Keras, etc).
• Ability to apply standard software development processes and clearly document results.
• Demonstrated ability to utilize remote sensing imagery for large-scale monitoring and/or modeling of agriculture and/or natural ecosystems.
• Excellent English language presentation and communication skills.
• Self-motivated, curious, and hands-on, with a proactive approach to problem-solving.
• Proven ability to work effectively in a remote, fast-paced, and collaborative environment.

Preferred Skills:

• Experience deploying ML models in scalable cloud-based environments (e.g., GCP, AWS, or Azure).
• Solid understanding of MLOps practices and experience in implementing them.
• Familiarity with containerization tools like Docker or Kubernetes.
• Knowledge of Google Earth Engine or similar geospatial data platforms.
• Background in agriculture-related domains, particularly crop monitoring.

Envision Yourself Here: Does this sound like your dream job? If so, go ahead and apply for the position and we’ll be in touch. We appreciate your interest in Regrow. While it may go without saying once you see the diversity on our current team, we encourage diversity on our team at all levels of the company. We are committed to fostering a diverse, inclusive environment and to encourage these values in everyone on our team. We provide an environment of mutual respect where opportunities are available without regard to race, color, religion, sex, pregnancy (including childbirth, lactation and related medical conditions), national origin, age, physical and mental disability, marital status, sexual orientation, gender identity, gender expression, genetic information (including characteristics and testing), military and veteran status, and any other characteristic protected by applicable law. We believe that diversity and inclusion for people from all walks of life is key to our success as a company.