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Tier-1 brand, metro location, mid-level ML role, and broad skill requirements increase candidate competition.
Requires specialized ML, MLOps, and recommender systems experience but skills are largely transferable across industries.
Explicit 4+ years plus mandatory ML, MLOps, big-data, and cloud skills make filters strict.
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Design, build, and operate scalable backend and ML systems for sponsored experiences, ranking, retrieval, and personalization at eBay scale.
Develop and own MLOps pipelines including CI/CD, training, validation, and monitoring of production-grade ML models.
Collaborate with Applied Researchers and Engineering teams to turn ML research and Generative AI prototypes into robust, low-latency production systems serving millions of users.
Bachelor's degree in Computer Science or related field.
4+ years of relevant work experience in ML, AI, or Data Engineering.
Experience with big data distributed processing frameworks (e.g., Hadoop, Spark, Flink) and ML frameworks like TensorFlow or PyTorch in production.
Proficiency in production software development in an object-oriented language (Scala, Java, Python) and building/managing CI/CD pipelines with containerization (Docker, Kubernetes).
Experienced in engineering scalable, distributed ML systems for large user bases with low-latency serving requirements.
Skilled at converting ML research and Generative AI prototypes into operating production services through close collaboration with Applied Researchers and product teams.
Familiar with cloud platforms, big data infrastructure, ML lifecycle automation (MLOps), and deploying ML models at scale via RESTful or gRPC APIs.