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Machine Learning Specialist
3 semanas atrás
BnBerry has been shaping the rental and housing industry for more than a decade. Now we are launching a disruptive travel-tech project where machine learning is the core engine, not a side tool.
We are looking for driven minds — people who live and breathe machine learning, who learn and build fast and who already proved it by building working projects, startups, or ambitious personal experiments.
Requirements- Proven experience building production systems around LLMs, especially fine-tuning and prompt engineering.
- Strong backend engineering skills in Python (FastAPI or similar), with ability to build service layers and interface with external APIs (e.g. OpenAI).
- Practical experience with vector databases like Pinecone, Weaviate, Qdrant, or FAISS — including document ingestion, indexing, and query ranking.
- Experience tracking and analyzing user behavior / feedback to extract ranking signals and patterns.
- Familiarity with embedding models, chunking strategies, and hybrid search logic.
- Ability to design and implement lightweight data pipelines for dynamic preference updates and context generation (e.g. Pandas, DuckDB, Airflow, etc.).
- Applied experience with computer vision: image classification, detection, segmentation, generative models.
- Experience combining vision and language models in real-world applications.
- Understanding of LLM fine-tuning and transfer learning (even if not used in this project).
- Experience with fast experimentation: A/B testing, ranking evaluation, or online learning approaches.
- You are passionate about ML and keep up with the latest research and frameworks.
- You build fast — startup prototypes, hackathon projects, ambitious personal work — and you ship.
- You are not buried in legacy stacks. Your skills are fresh, modern, and relevant.
- A short CV or summary about yourself.
- Description of ML project(s) you've worked on: scope, stack, and results.
- Bonus: link to GitHub, portfolio, or personal site.
- 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.
- Freedom & flexibility: fully remote setup, no corporate bureaucracy, focus on output not hours.
- 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.
