Senior AI Data Scientist (US Team)

Required:

• 3+ years of hands-on Data Science or ML Engineering experience

• Demonstrated experience building GenAI applications — RAG systems, LLM-powered pipelines, or agent frameworks in production or near-production settings

• Strong proficiency in classical ML: regression, classification, and model evaluation

• Proficiency in Python; experience with cloud platforms (AWS, GCP, or Azure)

• Fluent in both English and Spanish — you'll work with US clients and collaborate across our LATAM offices.

• Strong communication skills; comfortable presenting to non-technical stakeholders

Responsabilidades: • Design and build agentic AI systems — multi-step reasoning pipelines, tool-use agents, and orchestration frameworks (LangChain, LlamaIndex, or equivalent)

• Develop and deploy RAG architectures over structured and unstructured data sources, including document retrieval, embedding strategies, and LLM integration

• Build and productionize regression, classification, forecasting, and clustering models to drive measurable business outcomes

• Evaluate and improve LLM-based systems using structured evaluation frameworks (LLM-as-a-judge, retrieval quality, hallucination detection)

• Translate ambiguous client challenges into concrete analytical hypotheses and solution designs

• Build scalable data pipelines for ingestion, transformation, and model serving

• Communicate findings and recommendations clearly to both technical and non-technical stakeholders

Deseable: • Experience with computer vision (image classification, object detection, or multimodal models)

• Familiarity with vector databases (Pinecone, Weaviate, pgvector, or equivalent)

• Consulting or client-facing experience

• Knowledge of MLOps practices: model monitoring, versioning, CI/CD for ML

Beneficios: • Work on high-impact, real-world AI problems across industries from day one

• Be part of a founding remote team with direct access to US leadership

• Collaborative, technically rigorous culture with a strong knowledge-sharing ethos