Product Data Scientist

Position Overview

At Bloomfield, we are revolutionizing the way crops are monitored and managed using AI-powered imaging technology that provides continuous, plant-level insights from seed to harvest. In 2024, Bloomfield joined Kubota North America Corporation, uniting innovative technology with extensive agricultural expertise to empower farmers with smarter solutions.

Our AI team of engineers and scientists is evolving into specialized streams, and this role sits on a Product Stream focused on turning real-world plant imagery into reliable data products for growers. As an AI Engineer – Product Data Scientist, you will take requests from the Product team (e.g., “We are counting citrus; we want to estimate their weight.”) and drive the early phases of the ML lifecycle including data selection, annotation strategy, quality exploration, metric definition, and model selection and training.

Key Responsibilities

• Work closely with AI, Product, and Engineering teams to build AI products that deliver real value to customers.
• Own the early ML lifecycle: data exploration, curation, annotation strategy, metric design, model prototyping, and experimentation.
• Build quantitative and qualitative frameworks to describe plant behavior and crop characteristics.
• Translate raw plant imagery and sensor data into actionable business insights for specialty crops (e.g., citrus, grapes, berries).
• Partner with AI Platform and Data Engineering teams to integrate algorithms into the production data pipeline.
• Contribute to shaping our new AI Product Stream structure and workflows.

Required Qualifications

• Demonstrated ability to explore and analyze image data to design and implement the early stages of an ML model lifecycle, including data selection, exploration, cleaning, model design and training, and performance evaluation.
• Comfort working with real-world, messy data.
• Solid Python experience.
• Strong knowledge of Machine Learning and Computer Vision.
• Ability to design, conduct, and interpret experiments using appropriate statistical and scientific methods.
• A product mindset—willingness to iterate with users, analyze thousands of images, define metrics, and refine models.

Preferred Qualifications

• Knowledge of plant physiology, plant development, agronomy, or related discipline.
• Experience with high-throughput phenotyping, crop estimation, or yield prediction.
• Experience working with imagery or sensor data in agricultural environments.
• Experience in Deep Learning.
• Experience in C++.

Benefits & Perks

• Competitive base salary & bonus
• Opportunity to shape the future of AI in agriculture within a small, focused team backed by Kubota.