Senior AI Platform Backend

hace 4 días


Madrid, España Epam A tiempo completo

Senior AI Platform Backend (LLM)¿Quiere presentar una candidatura? Asegúrese de que su CV está actualizado y luego lea atentamente las siguientes especificaciones del puesto antes de solicitar.We are seeking a talented and proactive Senior AI Platform Backend Engineer (LLM) to lead the design, optimization and deployment of machine learning pipelines using MLOps in cloud environments. In this role, you will implement LLM-based solutions for chatbots and Retrieval-Augmented Generation (RAG) systems and develop robust DevOps / MLOps pipelines for production.RESPONSIBILITIESMaintain and enhance CI / CD pipelines using tools such as GitHub Actions, AWS CodePipeline, Jenkins or ArgoCDDesign and develop backend architecture for AI Verification and ChatGPT services utilizing Python and FastAPIBuild, optimize and scale classifiers and tools leveraging machine learning, encoders and rule-based modelsArchitect and implement solutions following Domain-Driven Design (DDD) and Test-Driven Development (TDD) best practicesDesign, develop, and maintain a production-grade LLM-as-a-judge service for verifying AI-generated content from source documents, leveraging frameworks such as HuggingFace Transformers, SpaCy, NLTK, and BM25Build and maintain high-throughput Retrieval-Augmented Generation (RAG) services, including ingestion pipelines and message brokersPerform prompt engineering, including techniques such as Chain-of-Thought and Few-Shot Learning, across various LLMs (OpenAI, Anthropic, Google, etc.)Provide hands‑on expertise and support for one or more leading AI frameworks (TensorFlow, Keras, PyTorch, BERT, etc.)Demonstrate technical leadership in at least one AI specialization, such as graph recommendation systems, deep learning or natural language processingREQUIREMENTSStrong proficiency in Python and experience developing backend services with FastAPIExperience building and maintaining CI / CD pipelines using tools such as GitHub Actions, AWS CodePipeline, Jenkins or ArgoCDHands‑on experience designing xsgfvud and optimizing scalable machine learning models, including classifiers, encoders and rule‑based systemsExperience working with large language models (LLMs) and frameworks such as HuggingFace Transformers, Spacy, NLTK and BM25Proven ability to design, develop and maintain high‑load Retrieval-Augmented Generation (RAG) services, including ingestion pipelines and message brokersWE OFFER- Private health insuranceEPAM Employees Stock Purchase Plan100 paid sick leaveReferral ProgramProfessional certificationLanguage coursesPython, FastAPI, AWS CodePipeline, Jenkins#J-18808-Ljbffr



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