ML Engineer

Bucharesthybridmid

Posted 4 days ago · via Recruitee

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About this role

Tech stack & ecosystem: (if applicable) You will be the backbone of our ML platform, building everything from user-facing interfaces down to the data layers that feed our models: Platform & API: Python, FastAPI, React, TypeScript. Data Warehousing & Storage: Google Cloud Platform (GCP), BigQuery, Cloud Storage, Apache Parquet / Arrow. Data & ML Orchestration: dbt, Apache Airflow, Kubeflow Pipelines (KFP), Asynchronous Job Queues (Celery/RabbitMQ). Unstructured Data & GenAI: Vector Databases (e.g., Pinecone, Weaviate), modern RAG tooling (LangChain, LlamaIndex). Data Quality & Contracts: Pydantic, Great Expectations, strict JSON Schema validation.…

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What we'd score you on

reqspace match rubric

Five dimensions, recruiter-grade. Upload your resume and we'll generate a written explanation of where you fit and where the gaps are.

Skills match

For this role: python, react, fastapi, restful, bigquery…

Level fit

This role is mid-level. We check your trajectory against it.

Domain experience

Your work in the role's domain matters more than your years total. We weight recent and direct experience.

Recency

A skill you used last quarter weighs more than one from five years ago. We grade on recency, not lifetime.

Location fit

This role is based in Bucharest. We weight your proximity and willingness to relocate.

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Skills in this role

Pulled from the job description. These are the keywords we'll weight when scoring your fit.

pythonreactfastapirestfulbigquerypineconeweaviategcpgoogle clouddockerrabbitmqairflowdbtpytorchlangchainllamaindexkubeflowvertex aigitjson

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