Software Engineer (Machine Learning)

Join our team as a Software Engineer specializing in Machine Learning. In this role, you will develop and improve user signals, features, and representations used by large-scale machine learning models for advertising and recommendation. You will explore machine learning approaches to learn effectively from large-scale, sparse, noisy, and heterogeneous user signals, and improve the quality, coverage, and utilization of user signals. You will also advance large-scale recommendation systems and explore new model architectures and learning approaches. Additionally, you will identify and solve challenging ML problems, scale machine learning models and training systems, and build scalable tools and frameworks for user signal and feature evaluation.

• Développer et améliorer les signaux utilisateur, les fonctionnalités et les représentations utilisées par les modèles d'apprentissage automatique à grande échelle pour la publicité et la recommandation.
• Explorer les approches d'apprentissage automatique pour apprendre efficacement à partir de signaux utilisateur à grande échelle, rares, bruyants et hétérogènes.
• Améliorer la qualité, la couverture et l'utilisation des signaux utilisateur, et mesurer leur impact sur les modèles d'apprentissage automatique en aval et la performance publicitaire.

• 4+ years of experience developing and deploying machine learning systems in production environments
• Bachelor's degree in Computer Science, Computer Engineering, Machine Learning, or a related technical field, or equivalent practical experience
• Strong programming and software engineering skills, with experience building reliable production systems
• Experience developing and training machine learning models using large-scale datasets
• Strong understanding of machine learning fundamentals, including model architectures, optimization, representation learning, feature engineering, and model evaluation
• Experience diagnosing and solving problems involving data and feature quality, model quality, training, or serving performance
• Experience with machine learning or deep learning in areas such as recommendation, ranking, retrieval, prediction, advertising, representation learning, or related applications
• Experience with modern deep learning frameworks such as PyTorch or TensorFlow
• Experience with large-scale recommendation or advertising systems, including candidate generation, retrieval, ranking, or prediction
• Experience developing user signals, features, or learned user representations for large-scale machine learning systems
• Experience with representation learning, embeddings, feature interaction, or multi-task learning using large-scale user signals
• Experience measuring the incremental value of user signals and understanding their downstream impact on ranking or recommendation performance
• Experience developing and scaling deep learning architectures for recommendation, ranking, or advertising applications
• Experience with distributed model training and large-scale ML infrastructure
• Experience optimizing training or inference workloads on GPUs or other accelerators
• Experience optimizing ML systems for latency, throughput, memory utilization, or computational efficiency
• Experience designing and analyzing online experiments and offline model evaluations