Software Engineer, Recommendation Systems

What you'll do

• Define architecture and technical strategy for recommendation systems, including retrieval, candidate generation, feature engineering, and ranking.
• Develop machine-learning methods and production infrastructure, and establish metrics and experimentation frameworks for recommendation quality.
• Lead cross-organizational modernization and engineering initiatives, while mentoring engineers and advising leadership.

What they ask for

• Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
• Experience defining technical strategy and architecture for large-scale machine-learning systems and leading cross-organizational initiatives.
• Experience developing and applying machine-learning models at scale, including experimentation design and metric definition.
• Proficiency with PyTorch or TensorFlow applied to large-scale recommendation models.

Nice to have

• Industry-recognized contributions to recommendation systems, information retrieval, or personalization through publications, patents, or open-source work.
• Experience building real-time feature serving, approximate nearest neighbor retrieval, or low-latency inference infrastructure at internet scale.

Pay

$271,000/year to $347,000/year USD base salary; bonus and equity amounts are not specified.

Tools

PyTorch, TensorFlow

AI focus

Applies novel machine-learning techniques to recommendations and rearchitects recommendation systems using AI-native approaches; promotes AI-native development practices.