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Machine Learning Specialist at Bnberry. 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.. . 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.). . . Bonus Skills (Highly Valued). . 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. . . Who We’re Looking For. . 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. . . . What We Expect From Your Application. . 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. . . . Company Location: Portugal.