Data Scientist

ScaleUp; Argentina; Remote; ARS 900,000 - 2,100,000; Full time

Job summary

SCALEUP in Argentina is seeking a Data Scientist to work with our research team on applied AI, infrastructure, and GenAI tooling initiatives focused on democratizing Generative AI.

This is a hands-on role for someone who enjoys working with modern AI tech, building practical tools, experimenting with new research, and contributing to open-source projects. Remote-first setup with collaboration across global teams.

Qualifications

• Strong Python development skills.
• Foundation in data structures, algorithms and math.
• Experience with PyTorch is preferred but not mandatory.
• Interest in applied AI and GenAI research.
• Willingness to contribute to open-source code.

Responsibilities

• Build RAG pipelines on top of internal documentation and knowledge bases.
• Develop Python libraries leveraging AWS services to enable GenAI capabilities for 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 common training issues.
• Develop visualizations to help understand model behavior and performance.

Skills

Python

Data structures

Algorithms

Engineering math

PyTorch

Open-source

English

Education

Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field

Job description

Data Scientist

• Location: Argentina — Remote


• Type: Full-time, long-term contractor


• Eligibility: This opportunity is open exclusively to candidates based in Argentina.

About the Company

Our client is a leading cloud-first consulting company delivering Managed Services, Staffing, and Professional Services. With a remote-first global team across North America, Europe, and Southeast Asia, the company helps organizations embrace cloud technologies through innovative, customer-focused solutions.

The organization values collaboration, agility, innovation, integrity, diversity and inclusion, and offers an environment where talented professionals can work on meaningful, cutting-edge initiatives.

About the Role

Our client is looking to hire a Data Scientist to work closely with senior members of its research team on applied AI, infrastructure, and tooling initiatives focused on democratizing Generative AI.

This is an excellent opportunity for someone who enjoys working hands-on with modern AI technologies, building practical tools, experimenting with new research, and contributing to open-source projects.

What You'll Do

• Build RAG pipelines on top of internal documentation and knowledge bases.




• Develop Python libraries leveraging AWS services to enable GenAI capabilities for large enterprises.




• Build and contribute to open-source internal tools.




• Implement neural-network architectures inspired by newly published research.




• Work with fine-tuned models, vector databases, embeddings, and related GenAI infrastructure.




• Create more realistic simulations to support AI agent training.




• Design automated tools to prevent common neural-network training issues, including overfitting, vanishing gradients, and dead ReLUs.




• Develop visualizations that help teams better understand model behavior and performance.

What We're Looking For

• Strong Python development skills.




• Solid foundation in data structures, algorithms, and engineering mathematics.




• Experience with PyTorch and deep neural-network training is preferred, but not mandatory.




• Genuine interest in applied AI, Generative AI, and emerging research.




• Interest in contributing to open-source code and tools.




• Strong engineering best practices and attention to code quality.




• Self-directed, independent, and comfortable working in a remote environment.




• Advanced English communication skills




• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field.