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Tier-1 brand, metro location, mid-level generalist ML role with broad skills increases competition.
Core ML, MLOps, and big-data engineering skills are highly transferable across industries.
Explicit 4+ years and required ML, MLOps, big-data, cloud skills make shortlisting strict.
Design, build, and operate scalable backend and ML systems for sponsored experiences, ranking, retrieval, and personalization at eBay scale.
Develop and own MLOps pipelines for continuous integration, delivery, training, validation, and monitoring of production-grade ML models.
Engineer data pipelines for model training and feature engineering, implementing and optimizing ML and Generative AI models for low-latency, high-throughput serving, collaborating with Applied Researchers to productionize prototypes.
Bachelor's degree in Computer Science or related field.
4+ years of relevant work experience in ML, AI, Data or Software Engineering.
Proficiency in OO programming languages (Scala, Java, Python).
Experience with big data distributed processing frameworks (Apache Hadoop, Spark, Flink), ML frameworks (TensorFlow, PyTorch), CI/CD pipeline management including containerization (Docker, Kubernetes), and cloud services (AWS, GCP, Azure).
Experienced in building scalable, distributed production systems exposing functionality via RESTful or gRPC APIs.
Strong operational knowledge of MLOps practices integrating continuous deployment and monitoring for ML models.
Capable of bridging machine learning research and robust production engineering in a high-scale e-commerce environment involving Generative AI and recommendation systems.