AgZen is tackling two of agriculture’s biggest challenges: waste and pollution by optimizing chemical application in real time, reducing input use, minimizing pollution, and protecting both yields and ecosystems.
Requirements
- 7+ years of experience in solving problems in computer vision/perception with a foundation in deep learning and ML
- Experience working with real-time or edge-based inference and integrating models with hardware or embedded systems.
- Deep experience training and validating computer vision models (e.g., object detection, segmentation, and classification) for robust performance in real-world environments.
- Proven ability to architect end-to-end computer vision pipelines, strategically decomposing complex problems across multiple models and stages.
- Expertise in MLOps best practices and tooling (e.g., MLflow, W&B, or similar experiment tracking and deployment frameworks) for managing the entire model lifecycle from research to production at scale.
- Advanced knowledge of software engineering principles, including software design, source control management, build processes, code reviews, and testing methods
- Advanced proficiency in Python, PyTorch, Numpy, and OpenCV.
Responsibilities
- Develop advanced computer vision models that support real-time detection and decision-making in AgZen’s spraying systems.
- Lead the design of model architectures, training pipelines, and evaluation methods that meet performance requirements in both lab and field environments.
- Collaborate closely with hardware, firmware, and product teams to ensure vision models integrate seamlessly with system components.
- Oversee data collection planning, dataset creation, and annotation quality to ensure robust and representative training data.
- Analyze field performance to identify root causes of model behavior, propose improvements, and validate updates through experimentation.
- Establish best practices for versioning, testing, deployment, and continuous improvement of computer vision models.
- Provide technical mentorship to teammates and contribute to strong engineering standards across the organization.
Other
- A bachelor’s degree in computer science, electrical engineering, robotics, or a related field; an advanced degree is preferred but not required.
- Clear communication skills and the ability to work effectively with cross-functional teams in a fast-moving environment.
- The resilience, adaptability, and technical leadership needed to deliver solutions in dynamic and sometimes unpredictable field conditions.
- Ability to operate effectively in dynamic field conditions
- Work required to be in-person in Somerville, MA (Boston area)
