Remote Data Scientist — GenAI & Open-Source Tools

Scale Up Recruiting Partners; Buenos Aires; Presencial; ARS 1.800.000 - 3.000.000; Jornada completa

Descripción de la vacante

Scale Up Recruiting Partners is seeking a Data Scientist to join a remote-first, Argentina-based team working on applied AI, infrastructure, and tooling to democratize Generative AI. You will collaborate with senior researchers to build practical tools and experiment with new research.

You’ll develop RAG pipelines, Python libraries with AWS, and contribute to open-source internal tools and models while emphasizing robust engineering and reliable model behavior.

Formación

• Bachelor’s degree in CS, Engineering, Information Systems, or related field.
• Strong Python and software engineering practices.
• Interest in Applied AI, Generative AI, and emerging research.
• Self-directed, remote-friendly work style.
• Solid foundation in data structures and algorithms.

Responsabilidades

• Build RAG pipelines on internal docs and knowledge bases.
• Develop Python libraries leveraging AWS for GenAI in large enterprises.
• Build and contribute to open-source internal tools.
• Implement neural-network architectures inspired by current research.
• Work with fine-tuned models, vector databases, embeddings, and GenAI infra.
• Create realistic simulations to support AI agent training.
• Design automated tools to prevent training issues (overfitting, vanishing gradients, dead ReLUs).
• Develop visualizations to help teams understand model behavior and performance.

Conocimientos

Python development

Data structures

Algorithms

Engineering mathematics

PyTorch experience

Open-source contributions

Code quality

Remote work

English communication

Educación

Bachelor’s degree in CS/Engineering/IS

Descripción del empleo

Scale Up Recruiting Partners is seeking a Data Scientist to join a remote-first, Argentina-based team working on applied AI, infrastructure, and tooling to democratize Generative AI. You will collaborate with senior researchers to build practical tools and experiment with new research.

You’ll develop RAG pipelines, Python libraries with AWS, and contribute to open-source internal tools and models while emphasizing robust engineering and reliable model behavior.