AI Engineer (Computer Vision)

TL;DR

AI Engineer (Computer Vision): Building computer vision and agentic systems to turn food waste data into operational intelligence for commercial kitchens with an accent on ML training pipelines and edge model deployment. Focus on designing rigorous cloud-side evaluation harnesses and developing LLM-driven features to provide procurement and operational insights.

Location: San Bruno, California

Salary: $240k – $280k base

Company

hirify.global is a waste prevention technology company reimagining food waste elimination through smart systems and infrastructure.

What you will do

• Build and manage end-to-end ML training pipelines, including data ingestion and ground truth generation.
• Train and evaluate segmentation, classification, and mass-estimation models using ConvNets and VLMs.
• Develop cloud-side evaluation harnesses to monitor edge model performance in the field.
• Manage MLOps, including experiment tracking, model versioning, and automated evaluation.
• Optimize and validate models for deployment to edge devices.
• Design LLM- and agent-powered features for customer-facing recommendations.

Requirements

• Strong fundamentals in computer vision and deep learning (segmentation, detection, classification).
• Fluency with VLMs, LLMs, and agentic systems alongside classical deep learning.
• Experience building scalable ML training pipelines and data annotation systems.
• Proficiency with AWS cloud ML infrastructure.
• Experience with cloud-to-edge model deployment.
• Must be based in San Bruno, California.

Nice to have

• Experience with video understanding and temporal consistency.
• Experience using foundation models for data annotation.
• Proficiency with MLOps tools like Weights & Biases, MLflow, or SageMaker.
• Background in Hardware/IoT products and embedded CV systems.

Culture & Benefits

• Mission-driven environment focused on sustainability and food waste reduction.
• Opportunity to work in a small, high-impact AI team.
• Focus on building beautifully designed, easy-to-use technologies.
• Potential for equity grants and comprehensive benefits.