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Topsort is a global Commerce AI company building advanced advertising and AI-powered technology for retailers and marketplaces across 40+ countries. The company develops intelligent systems for smarter advertising, real-time auctions, and product discovery.
You'll join the T-Brain team, Topsort's AI platform that develops machine learning models powering predictions, recommendations, and decision-making across retail environments. This role sits at the intersection of Machine Learning, Data Science, and Software Engineering.
Key responsibilities include:
• Design, train, evaluate, and improve ML models for predictions, recommendations, and commerce applications
• Design and run experiments, including A/B testing, to evaluate model performance and make statistically grounded decisions
• Build, deploy, and maintain reliable ML solutions using cloud infrastructure, ensuring scalability and performance
• Work with complex datasets to identify patterns, develop predictive models, and improve model effectiveness
• Contribute to development of large-scale foundation models and explore how experimental findings apply across use cases
Success means delivering production-ready models reliably deployed at scale, validated improvements supported by sound statistical evidence, consistent performance gains in accuracy and relevance, scalable solutions adaptable across clients and retail use cases, and continuous improvement informed by monitoring and changing data patterns.
The company values ownership, engineering judgment, collaboration, curiosity, and attention to detail. You'll work in a high-bar engineering environment where systems built matter and you're expected to leave systems better than you found them.
REQUIREMENTS:
• 5+ years of experience in Machine Learning Engineering, Applied Machine Learning, or Data Science, with hands-on production deployment experience
• BSc degree in Computer Science, Software Engineering, Mathematics, Statistics, or related quantitative field
• Strong experience developing, training, evaluating, and optimizing ML models for real-world applications
• Hands-on experience with cloud platforms (AWS, GCP, or Azure) including model training, deployment, and scalable ML pipelines
• Strong Python skills and experience with SQL, data processing, and large datasets
• Solid statistical foundations and practical experience designing, running, and interpreting A/B tests
• 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 (neural networks, transformers) using PyTorch or TensorFlow
• Familiarity with emerging ML research and applying new techniques to practical problems
