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Job Description
Structured overview of role & requirementsAbout This Role
Design, build, and operate scalable backend and machine learning systems for sponsored experiences, ranking, retrieval, and personalization.
Develop and own MLOps pipelines including CI/CD, training, validation, and monitoring of production ML models.
Engineer robust big data pipelines and APIs to serve AI models including Generative AI (LLMs) at eBay scale, ensuring system reliability and low-latency performance.
Minimum Requirements
MS in Computer Science or related field with 5+ years relevant experience OR BS/BA with 6+ years in ML/AI/Data Engineering.
Expertise in production software engineering with OO languages such as Scala, Java, or Python.
Extensive experience with big data distributed processing (e.g., Hadoop, Spark, Flink) and ML frameworks like TensorFlow and PyTorch.
Experience building and managing CI/CD pipelines, containerization (Docker, Kubernetes), and cloud services (AWS, GCP, Azure).
Ideal Candidate Profile
Experienced in operationalizing machine learning models and infrastructure in production, including monitoring and incident response in live 24/7 environments.
Strong background in both software engineering and machine learning systems, with an ability to translate research prototypes into production-ready, scalable solutions.
Familiarity with serving frameworks for ML/LLM (e.g., TensorFlow Serving, TorchServe, Triton) and with building APIs for large scale machine learning applications.