Machine Learning Engineer
At Orchard, we’re securing America’s food supply by building the AI Farmer that automates our nation’s farms. We are the industry leader, growing rapidly, and backed by more than $25 million from leading investors, including Quiet Capital, Shine Capital, and General Catalyst.
Every year, hundreds of billions of dollars in crop value are lost because critical farming decisions are made using incomplete and imprecise data. We’re building the technology to change that.
Our AI-powered camera systems mount to tractors and scan millions of trees, vines, and plants, capturing precise data on yield estimates, fruit size, crop health, disease, and more. We train edge vision AI models that analyze every plant and determine exactly what interventions and treatments it needs. That intelligence flows into FruitScope OS, our farm-management platform, where growers can understand their crops, make better decisions, and direct operations in the field.
Today, Orchard’s technology is trusted by some of our nation’s largest farms. They use our products to grow higher-quality crops while reducing chemical use and operating costs, helping them farm more profitably and sustainably than ever before.
Our Culture:
Unshakeable Resilience - Our customers feed millions of people, and our customers depend on us. We are ultra-hardworking, never give up, and we do whatever it takes.
Always Keep Moving - We move fast, waste no time, and have an extreme bias towards action. Progress compounds every day, and our impact is measured in decades.
Improve Everything - At 1% success, we save millions of pounds of food from going to waste. If we are 100% successful we will impact the lives of billions of people across the world.
Farmers First - Every team member spends at least a few days in the fields with our farmers each month.
No Job Beneath Us - We’re low ego, own every outcome, and are all working towards the same goal.
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.
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!