The role involves building and optimizing production ML systems for large-scale recommendation, search, ads ranking, and GenAI applications
Job Summary
The role involves building and optimizing production ML systems for large-scale recommendation, search, ads ranking, and GenAI applications.
Engineers will own the full ML lifecycle including data, training, serving, and experimentation at over 10 million QPS.
Candidates must collaborate with ML Scientists, Backend Engineers, and Product teams to ship models that directly impact engagement and conversion metrics.
Matching Summary
Match Score: 75
The role involves building and optimizing production ML systems for large-scale recommendation, search, ads ranking, and GenAI applications.
Skills & Requirements
Must-have
Python, Go, or C++ proficiency
PyTorch or TensorFlow experience
Spark, Flink, Kafka data processing
Docker and Kubernetes knowledge
AWS, GCP, or Azure cloud platforms
Nice-to-have
Large-scale recommender systems experience
LLM inference service optimization
GPU programming and CUDA expertise
E-commerce or social media background
Online learning and RL familiarity
Key Requirements
BS/MS in Computer Science or Engineering
1+ years shipping ML models to production
Strong software engineering skills in data structures and algorithms