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Tier-1 brand, metro location, generalist title, mid-level experience, and broad skill requirements increase competition.
Requires ML platform, MLOps, and big-data infrastructure expertise, limiting cross-industry transferability.
Explicit 5+ years plus mandatory ML/MLOps, cloud, and big-data stack makes shortlisting highly strict.
Lead and coordinate technical activities for machine learning platform projects, ensuring achievement of operational and customer objectives.
Design, build, and optimize ML pipelines and data infrastructure to support ML lifecycle and model deployment across PayPal domains.
Collaborate with management to improve engineering standards and represent PayPal externally with partners and industry organizations.
5+ years relevant experience with a Bachelor’s degree or equivalent combination of education and experience.
Strong proficiency in machine learning concepts, algorithms, and hands-on experience developing and deploying ML models.
Proficiency in programming languages such as Python, Go, Java and experience with ML frameworks like TensorFlow, PyTorch, and scikit-learn.
Experience with cloud platforms (AWS, Azure, GCP), containerization (Docker, Kubernetes), and ML infrastructure or MLOps platforms.
Experienced in building and optimizing scalable ML infrastructure and pipelines in complex, multi-domain environments.
Capable of making strategic technical decisions balancing time, quality, complexity, and risk while improving processes and standards.
Skilled in cross-functional collaboration and mentoring, with the ability to represent the company externally and influence stakeholders effectively.