AI Engineer (Image Analysis & Evaluation)

  • Компания: Bnberry
  • Город , ,
  • Зарплата:
  • Размещено: 2026-01-02 20:27:44

Описание

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.

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