AI Engineer (Image Analysis & Evaluation)
Bnberry
Posted: January 2, 2026
Interested in this position?
Create a free account to apply with AI-powered matching
Quick Summary
We are looking for an experienced AI Engineer with hands-on experience in working with photographs using machine learning to develop and optimize image analysis and evaluation pipelines. The ideal candidate will have expertise in image quality assessment, ranking, and enhancement tasks using modern ML models like Vision-1 and Nano Banana Pro, and be able to build and iterate on AI-driven image pipelines based on real-world data.
Required Skills
Job Description
We are looking for an AI Engineer with hands-on experience in working with photographs using machine learning. The focus of this role is image understanding, evaluation, ranking, and optimization.
What you will work on
• Analysis and evaluation of images using AI models
• Image quality assessment and ranking
• Developing and training models that can objectively evaluate photos
• Image enhancement tasks: quality improvement, color correction, visual consistency using modern ML models (Like vision-1, Nano Banana Pro)
• Building and iterating on AI-driven image pipelines based on real-world performance
Requirements:
• Proven experience working with images using AI / ML
• Strong understanding of computer vision techniques for image reading, evaluation, and comparison
• Experience training and fine-tuning models for image-related tasks
• Practical knowledge of image quality metrics and evaluation approaches
• Understanding of how image quality impacts user behavior and business outcomes
• Motivation to work deeply with visual data and improve it in measurable ways
Experimentation & analytics
• Experience with A/B testing and experimentation frameworks
• Ability to design experiments to validate model decisions using real metrics, not subjective judgment
• Understanding how to analyze experiment results and iterate based on data
• Experience optimizing models and image pipelines through continuous measurement and testing
Nice to have
• Familiarity with large-scale image datasets
• Experience or familiarity with frameworks like LangChain or similar agent-based orchestration tools
• Understanding how LLMs and agents can be integrated into ML pipelines (e.g. evaluation, orchestration, metadata enrichment)
• Experience deploying and maintaining ML models in production
Benefits:
• Work on a revolutionary product at the intersection of travel and machine learning.
• Direct impact: your models go to production and shape the core of the product, not stay in research slides.
• Fast growth environment: exposure to modern ML stacks (transformers, multimodal ML, computer vision) with constant room to experiment.
• Ownership: you’ll have autonomy in decision-making and the chance to influence product direction.
• Flat team structure: work directly with founders and senior engineers, no endless management layers.
• Visibility: your contributions will be recognized, not lost in a big company hierarchy.