Applied AI/ML Engineer (Data Scientist)

FutureProofing; Buenos Aires; Remote; ARS 131,726,000 - 193,714,000; Full time

Job summary

FutureProofing is seeking an Applied AI/ML Engineer to design, implement, and ship production-ready AI solutions within client product teams. This remote, contract role emphasizes ownership and high engineering standards.

You will train and evaluate models, build end-to-end pipelines, deploy to production, and collaborate with cross-functional partners. Experience with ML frameworks and data workflows is essential, with a focus on scalable, cost-aware solutions.

Qualifications

• Strong foundation in computer science and algorithms.
• Experience with pattern recognition and statistics for real-world data analysis.
• Hands-on experience with neural networks and modern ML frameworks for training, deploying, and monitoring models.
• Proficiency in at least one modern programming language (Python, Go, Java, or C++).
• Experience deploying models to production environments and working with data pipelines and APIs.
• Ability to communicate effectively in remote, cross-functional teams and take ownership.

Responsibilities

• Experiment with algorithms, train and evaluate models.
• Develop end-to-end ML pipelines and integrate AI components into client products.
• Optimize performance for scalability, reliability, and cost.
• Contribute to code reviews, documentation, and architecture discussions.
• Maintain high engineering standards and continuously improve tooling and workflows.
• Take ownership of deliverables and ensure blockers are resolved quickly.

Skills

Computer Science fundamentals

Pattern Recognition

Statistics for data analysis

Neural networks & ML frameworks

Python · Go · Java · C++

CI/CD & software engineering practices

Remote collaboration

Education

Bachelor’s or advanced degree in CS/Math/Engineering

Equivalent practical experience

Tools

PyTorch

TensorFlow

JAX

Job description

Company Description

FutureProofing builds production-grade AI systems by embedding exceptional senior engineers directly into teams delivering real AI products. The company focuses on end-to-end ownership, rigorous engineering practices, and engineers who operate as true teammates from day one. Through its Remote Engineering Operating System, FutureProofing ensures client-grade communication, behavior standards, and delivery structure for remote work. Engagements feature engineers shipping within the first week, weekly summaries on progress and upcoming work, and a consistent bar for ownership, craft, clarity, and impact. FutureProofing is committed to eliminating stalled demos and non-production prototypes, focusing instead on predictable delivery of high-quality AI systems.

Role Description

As an Applied AI/ML Engineer at FutureProofing, you will design, implement, and ship production-ready AI and machine learning solutions within client product teams. In this remote, contract role, you will work closely with cross-functional partners to understand requirements, select appropriate models, develop end-to-end pipelines, and integrate AI components into existing systems. Your day-to-day activities will include experimenting with algorithms, training and evaluating models, performing data analysis, and optimizing performance for scalability, reliability, and cost. You will contribute to code reviews, documentation, and architecture discussions, and follow FutureProofing’s communication cadence to provide clear updates, highlight risks, and ensure blockers are resolved quickly. You will be expected to take ownership of deliverables, maintain high engineering standards, and continuously improve tooling and workflows for applied AI development.

Qualifications

• Strong foundation in Computer Science and Algorithms, with experience building scalable, maintainable software systems.
• Practical expertise in Pattern Recognition and Statistics for real-world data analysis, feature engineering, and model evaluation.
• Hands-on experience with Neural Networks and modern ML frameworks (e.g., PyTorch, TensorFlow, JAX) for training, deploying, and monitoring models.
• Proficiency in at least one modern programming language commonly used in AI/ML (e.g., Python, Go, Java, or C++), and familiarity with software engineering best practices (testing, CI/CD, version control).
• Experience deploying models to production environments (cloud services, containers, microservices) and working with data pipelines and APIs.
• Ability to communicate clearly in remote, cross-functional teams, with a track record of ownership, reliable delivery, and proactive problem-solving.
• Bachelor’s or advanced degree in Computer Science, Mathematics, Engineering, or a related field, or equivalent practical experience.
• Prior experience in applied AI/ML roles shipping production systems; familiarity with MLOps, monitoring, and model lifecycle management is a plus.