AI Engineer

present of AI; Santiago; Hybrid; CLP 25,000,000 - 40,000,000; Full time

Job summary

Topsort is seeking an AI Engineer to help build AI inside live advertising systems in Santiago, Chile. The role focuses on implementing models that run with low latency, handle cookieless signals, and perform well in real-time auctions.

You will collaborate with data and software teams to deliver production-ready solutions. The candidate should have strong Python and ML experience, with hands-on training, evaluation, and deployment skills, and a focus on privacy-aware data handling.

Qualifications

• Solid Python and ML library experience.
• Experience taking models from experiments to production.
• Hands-on model training, evaluation and deployment.
• Ability to collaborate with data and software teams.
• Responsible for privacy-aware data handling.

Responsibilities

• Build AI inside live advertising systems to run fast with low latency.
• Keep models accurate in cookieless retail media and real-time ad auctions.
• Ensure data quality and robust monitoring of model behavior.

Skills

Python

ML libraries

Model training

Evaluation

Monitoring

Privacy aware data

Job description

AI & Data · Santiago, Santiago Metropolitan Region, Chile

An AI Engineer role typically asks for solid Python and machine learning skills, plus the ability to take models from experiment to production. A strong candidate brings hands on experience with model training, evaluation and deployment, and can work closely with data and software teams. Here the work centers on building intelligence for cookieless retail media and real time ad auctions, so care with data quality and low latency thinking matters.

How it fits the AI era

This kind of role sits close to the core of how AI changes software, since models increasingly drive targeting, bidding and measurement decisions. The human parts that remain are framing the right problem, judging whether outputs are sound, and owning the tradeoffs when systems act at speed. The engineer still decides what good looks like and when a model should not be trusted.

How it builds AI experience

The role offers a chance to build AI inside live advertising systems, where models must run fast and handle sparse or shifting data. Useful preparation includes projects on recommendation, ranking or bidding style problems, and practice with model evaluation under real constraints. Working with cookieless signals is a growing area, so showing care with privacy aware data handling helps.

Worth showing

• Python and ML libraries
• Ranking or bidding projects
• Evaluation and monitoring
• Privacy aware data handling

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

About Topsort

AI and machine-learning infrastructure for cookieless retail media networks and real-time advertising auctions, per the company.