AgZen

HQ
Somerville
17 Total Employees
Year Founded: 2022

Jobs at AgZen

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Recently posted jobs

2 Days AgoSaved
Remote
USA
Computer Vision • Hardware • Machine Learning • Robotics • Agriculture
Own the customer journey for AgZen’s precision agriculture products, including pre-sale technical support, hardware installation, software configuration, grower training, in-season optimization, troubleshooting, and post-sale support. Develop dealer capabilities, manage partner relationships, document field activity, and provide product feedback. The role is remote but requires extensive multi-state travel, outdoor fieldwork, and collaboration with growers, dealers, sales teams, and product teams.
One Month AgoSaved
In-Office
Somerville, MA, USA
Computer Vision • Hardware • Machine Learning • Robotics • Agriculture
Own cloud-native MLOps infrastructure for multimodal sensor data ingestion, processing, labeling, validation, model traceability, deployment gates, monitoring, drift detection, and diagnostics. Partner with data scientists, ML engineers, and stakeholders to ensure reliable pipelines, fresh features, robust model performance, and effective post-deployment metrics. Build visualization and support tools that help technical and nontechnical users understand perception and recommendation systems.
One Month AgoSaved
In-Office
Somerville, MA, USA
Computer Vision • Hardware • Machine Learning • Robotics • Agriculture
Design, build, and maintain infrastructure, internal tools, and platforms supporting computer vision systems deployed on agricultural sprayers. Scale distributed edge systems, connect firmware, machine learning, and user interfaces, manage cloud and bare-metal infrastructure, and test solutions in hardware-equipped environments.
One Month AgoSaved
In-Office
Somerville, MA, USA
Computer Vision • Hardware • Machine Learning • Robotics • Agriculture
Analyze crop protection and sensor data, develop statistical and machine learning models, build dashboards and recommendation engines, improve perception pipelines, establish data quality measures, and communicate findings across technical and agricultural teams.