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.

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📌 AI Engineer (Santiago)
🏢 present of AI
📍 Santiago