Senior Machine Learning Engineer

We are looking for a Senior 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: - As an early engineer, you'll receive generous equity

compensation - Full-time role at our San Francisco, CA office - Flexible working hours - 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. - Stay up-to-date with current literature in computer vision models and architectures, and apply relevant advancements to our systems. - Develop, deploy, and monitor 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. - 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: - 5+ years of experience building production-grade data pipelines and ML infrastructure. - Proficiency in Python and experience with ML frameworks (e.g., TensorFlow, PyTorch). - Strong experience with data engineering tools (e.g., Pandas, SQL, Apache Airflow, Spark). - Familiarity with cloud platforms (AWS, GCP, or Azure) 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!