AI Engineer
TopsortRetail Media company
Santiago, ChileSenior
FJ Labs
Pear VC
Quiet Capital
Upload Ventures
W23 Global
Data & AINew
About the role
TL;DR
Build and deploy AI models for commerce applications, focusing on predictions and recommendations.
- •Come build what's next with Topsort! About Topsort Topsort is a global Commerce AI company making advanced advertising and AI-powered technology accessible to businesses of all sizes.
- •Our technology helps retailers and marketplaces grow through smarter advertising, real-time auctions, and intelligent product discovery.
- •With a presence in 40+ countries and a growing international team, we're building the technology behind the next generation of commerce.
- •What Is This Role Like? We're looking for an AI Engineer to join our T-Brain team and help build the intelligence powering the next generation of commerce.
- •T-Brain is Topsort's AI platform, developing machine learning models that power predictions, recommendations, and smarter decision-making across retail environments.
- •In this role, you'll work at the intersection of Machine Learning, Data Science, and Software Engineering, developing models, running experiments, and turning complex data into scalable, production-ready solutions.
- •What You'll Own Machine Learning Development: Design, train, evaluate, and improve ML models for predictions, recommendations, and other commerce applications.
- •Experimentation & Validation: Design and run experiments, including A/B testing, to evaluate model performance and make statistically grounded decisions.
- •Production ML: Build, deploy, and maintain reliable ML solutions using cloud infrastructure, ensuring scalability and performance.
- •Data & Modeling: Work with complex datasets to identify patterns, develop predictive models, and improve model effectiveness.
- •Model Innovation: Contribute to the development of large-scale foundation models and explore how experimental findings can be applied across different use cases.
- •What Success Looks Like Production-Ready Models: ML models are reliably deployed, maintained, and performing at scale in production environments.
- •Validated Improvements: Experiments demonstrate measurable improvements against established baselines, supported by sound statistical evidence.
- •Model Performance: Predictions and recommendations deliver consistent, measurable improvements in accuracy, relevance, or other defined performance metrics.
- •Scalable Solutions: Models and experimental findings can be adapted and extended across different clients and retail use cases.
- •Continuous Improvement: Monitoring, experiment results, and changing data patterns inform ongoing improvements in model performance and reliability.
- •What You'll Bring Don't check every box? We'd still love to hear from you.
- •We value curiosity, strong judgment, and people who take ownership of results: Relevant Experience: 5+ years of experience in Machine Learning Engineering, Applied Machine Learning, or Data Science, with hands-on experience deploying models in production.
- •Academic Background: BSc. degree in Computer Science, Software Engineering, Mathematics, Statistics, or a related quantitative field.
- •Machine Learning: Strong experience developing, training, evaluating, and optimizing ML models for real-world applications.
- •Cloud ML: Hands-on experience with cloud platforms such as AWS, GCP, or Azure, including model training, deployment, and scalable ML pipelines.
- •Python & Data: Strong Python skills and experience with SQL, data processing, and working with large datasets.
- •Experimentation: Solid statistical foundations and practical experience designing, running, and interpreting A/B tests to evaluate model performance.
- •Software Engineering: Strong coding practices and experience building reliable, maintainable, production-ready ML systems.
- •Nice To Have: Experience in e-commerce, Retail Media, AdTech, or personalization.
- •Experience with recommendation systems, search relevance, retrieval, or ranking models.
- •Familiarity with deep learning architectures, including neural networks and transformers, using frameworks such as PyTorch or TensorFlow.
- •Familiarity with emerging ML research and experience applying new techniques to practical problems.
- •Who Thrives Here We set a high bar for engineering because the systems we build matter.
- •You'll thrive here if you: Ownership & Quality: You take responsibility for what you build, write production-ready code, and leave systems better than you found them.
- •Engineering Judgment: You make thoughtful technical decisions, communicate tradeoffs honestly, and balance speed with long-term reliability.
- •Collaboration & Communication: You share knowledge, communicate openly, and work effectively across teams to solve complex challenges.
- •Curiosity & Attention to Detail: You care about the details, continuously improve your skills, and explore new technologies with a critical mindset.
- •We are proud to be an equal opportunity employer and to foster a workplace where diversity is valued and celebrated.
- •We believe that diverse perspectives and experiences strengthen our teams and drive better outcomes.
- •We respect and value any race, religion, color, national origin, ancestry, caste, gender, gender identity or expression, sexual orientation, age, disability, medical condition, pregnancy, genetic information, marital status, or military service.
- •Do you sound like the right fit? Let's dive right in!
Required skills
PythonSQLAWSGoogle CloudAzureTensorFlowPyTorchscikit-learnA/B Testing
Nice-to-have skills
NLPLLMs
Domain expertise
ecommerceadtechretail
Tech stack
PythonSQLAWSGoogle CloudAzureTensorFlowPyTorchscikit-learnKerasKubeflowSageMakerVertex AI