Senior AI Data Scientist (US Team)
Artefact LatAm
· Remote
Full time
$2200 - $3300
🤖 Machine Learning
Today
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What We're Looking For
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
What You'll Do
- 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
Preferred:
- 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
Why Join Us
- 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
Machine LearningPythonCloud Platforms
Source: GetOnBoard