BnBerry is hiring a Machine Learning Specialist to build production systems around LLMs as the core engine of a disruptive travel-tech project. You'll focus on fine-tuning, prompt engineering, backend services, and data pipelines to have a direct impact on the product.

What You'll Do

Build production systems around LLMs, especially fine-tuning and prompt engineering.
Build service layers and interface with external APIs using Python (FastAPI or similar).
Work with vector databases for document ingestion, indexing, and query ranking.
Track and analyze user behavior and feedback to extract ranking signals and patterns.
Design and implement lightweight data pipelines for dynamic preference updates and context generation.

What We're Looking For

Proven experience building production systems around LLMs, especially fine-tuning and prompt engineering.
Strong backend engineering skills in Python (FastAPI or similar).
Ability to build service layers and interface with external APIs like OpenAI.
Practical experience with vector databases like Pinecone, Weaviate, Qdrant, or FAISS.
Experience tracking and analyzing user behavior and feedback to extract ranking signals.
Familiarity with embedding models, chunking strategies, and hybrid search logic.
Ability to design and implement lightweight data pipelines for dynamic updates (e.g., Pandas, DuckDB, Airflow).
Passion for ML and keeping up with the latest research and frameworks.
Ability to build fast and ship projects (startup prototypes, hackathon projects, personal work).
Fresh, modern, and relevant skills, not buried in legacy stacks.

Nice to Have

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.
Experience with fast experimentation: A/B testing, ranking evaluation, or online learning approaches.

Technical Stack

Python, FastAPI, OpenAI
Pinecone, Weaviate, Qdrant, FAISS
Pandas, DuckDB, Airflow

Team & Environment

Flat team structure. Work directly with founders and senior engineers, no endless management layers. The culture is built by driven minds who live and breathe machine learning, learn and build fast, with a focus on shipping and output.

Benefits & Compensation

Work on a revolutionary product at the intersection of travel and machine learning.
Direct impact: models go to production and shape the core of the product.
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: autonomy in decision-making and chance to influence product direction.
Flat team structure: work directly with founders and senior engineers.
Visibility: contributions recognized, not lost in a big company hierarchy.