The Role:In order to analyze billions of fruit on farms all year long, our advanced, tractor-mounted camera systems have to know a.) precisely where they are, and b.) everything about the fruit they are seeing.
We are looking for a Machine Learning Engineer to
build creative, practical, and robust solutions to ML/CV software and infrastructure problems, relating to training edge ML models on massive amounts of real-world farm image data collected by our camera systems.
About the role: - Full-time, in-person role at our San Francisco or Seattle office.
- As an early engineer, you'll receive generous equity compensation
- Comprehensive Health, Vision, and Dental coverage, and we cover 100% of the premium
- We move fast, and sometimes this means staying late or working weekends
- Our team is close-knit & highly driven, you'll work directly with our CEO and entire team
- We're deeply motivated by the impact we're making - every line of code written or new system built means less food that goes to waste, and more people who are fed.
What you'll do:- Build and maintain scalable ETL pipelines for processing large, diverse image datasets collected from our tractor-mounted camera systems in farms.
- Develop and deploy infrastructure for model training, evaluation, and inference, both in the cloud and on edge devices.
- Design and implement intelligent active sampling infrastructure to optimize data collection and improve model performance.
- Stay up-to-date with current literature in computer vision models and architectures, and apply relevant advancements to our systems.
- Collaborate with a multidisciplinary team to integrate ML solutions into production robotics systems.
- Work closely with agronomists and farmers to understand crop biology and translate domain knowledge into actionable ML features.
- Be a generalist, supporting different parts of our software stack as needed.
What makes you a good fit:- 2+ years of real-world, industry experience building production-grade data pipelines and ML infrastructure.
- Proficiency in Python and experience with ML frameworks (e.g., PyTorch).
- Strong experience with data engineering tools (e.g., Pandas, SQL, MLFlow, WandB).
- Familiarity with cloud platforms (AWS, GCP) and containerization (Docker, Kubernetes).
- Experience working with massive amounts of real-world training data.
- Familiarity with MLops software and data engineering to ensure consistent deployment of ML models.
- Ability to work independently, learn quickly, and operate in a dynamic environment
- Enthusiasm for taking on multiple roles and responsibilities as our company grows.
Bonus Points:- Experience deploying & optimizing ML models to run fast on embedded compute like NVIDIA Jetson
- Experience prototyping, evaluating, or deploying new ML/CV models on the edge.
If you're looking to help make a positive impact in the world by building the future of farming, come join us!
