AgZen is tackling two of agriculture’s biggest challenges: waste and pollution. Billions are spent on pesticides and fertilizers, yet most never reach the crops - resulting in costly waste and significant environmental harm. AgZen optimizes chemical application in real time, reducing input use, minimizing pollution, and protecting both yields and ecosystems.
Requirements
- 3+ years of experience developing algorithms and solving problems in computer vision/perception.
- 2+ years of experience developing production machine learning systems.
- Advanced proficiency in Python, PyTorch, Numpy, and OpenCV.
- Strong foundation in machine learning, deep learning, and modern computer vision techniques.
- Experience working with robotics systems that use perception and AI components.
- Adept with the latest research in perception and machine learning, demonstrated by activity in the research community (e.g., reading conference papers, publications).
- Experience with MLOps, data pipelines, and deploying models to production environments.
- Familiarity with embedded systems and optimizing models for edge devices.
Responsibilities
- Implement deep-learning models for tasks including object segmentation, classification, optical flow, and 3D reconstruction.
- Architect and build new end-to-end models, potentially merging existing networks for improved performance.
- Employ techniques like quantization to enable power-efficient model execution on edge devices.
- Develop innovative methods to improve model accuracy and inference speed in edge deployment scenarios.
- Collaborate with the software engineering team to architect and develop data processing and annotation pipelines for continuous system improvement.
- Stay at the forefront of AI research by exploring and applying advancements in CNNs, transformers, and model quantization.
Other
- This role is located in Somerville, MA (Boston area) with work required to be in-person.
- Master’s/PhD degree or equivalent experience in Computer Science, Robotics, or a related field.
- Passionate, genuinely curious, and excels in a fast-paced, team-centric environment where they can build new technologies that integrate different fields.
