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Visor.ai logo
Visor.ai

No-code Conversational AI Platform for Customer Service Automation. Smart Interactions and Workflows made easy.

Data Scientist

Data ScientistData ScientistFull TimeRemoteJuniorTeam 51-200Since 2016H1B No SponsorCompany SiteLinkedIn

Location

Portugal

Posted

109 days ago

Salary

0

Seniority

Junior

Bachelor Degree1 yr expEnglishMicroservicesPandasPythonscikit-learn

Job Description

Data Scientist

Visor.ai

• Design and develop end-to-end NLP pipelines — from classical text processing to state-of-the-art LLM-powered architectures • Build and maintain systems for intent detection, NER, entity extraction, and text classification, both standalone and as components feeding into larger LLM workflows • Design and optimize Retrieval-Augmented Generation (RAG) systems — chunking strategies, vector store architecture, hybrid search (dense + sparse), and re-ranking pipelines • Work with embedding models for semantic search, document retrieval, and intent classification in contact center contexts • Design and implement agentic architectures — tool use, function calling, multi-step reasoning, and orchestration with frameworks like LangChain, LlamaIndex, or custom-built solutions • Develop memory and context management strategies — short-term conversation memory, long-term user context, and context window optimization for multi-turn interactions • Evaluate and benchmark models rigorously: hallucination detection, faithfulness scoring, latency/token cost tradeoffs, and continuous performance monitoring • Integrate AI components into scalable, production-ready microservices with a focus on low-latency inference pipelines • Collaborate with product and engineering to design new AI-powered features and drive innovation across the platform • Conduct practical research with a scientific mindset and a focus on delivery — publications are possible and encouraged

Job Requirements

  • 1-3 years of experience in a Data Science, AI or NLP Engineer role
  • Strong programming skills in Python and core Data Science & ML libraries (Pandas, scikit-learn, NLTK, spaCy, Gensim)
  • Solid understanding of NLP fundamentals — word embeddings, NER, information extraction, intent classification, text similarity
  • Experience building and delivering ML products in production environments
  • Hands-on experience with LLMs in production (OpenAI, Anthropic, Mistral, LLaMA, Gemini, or equivalent)
  • Familiarity with RAG pipelines
  • Experience with vector databases (Pinecone, Weaviate, Qdrant, pgvector, etc.) and modern embedding models
  • Understanding of context window management, token budgeting, and prompt design for multi-turn conversations
  • Experience with LLM Observability and Monitoring
  • Experience with LLM frameworks such as LangChain, LlamaIndex, or Hugging Face Transformers

Benefits

  • Competitive compensation package
  • Health insurance
  • Career growth opportunities
  • Access to training, events, and conferences
  • Remote First model

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