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Recognizable global brand, mid-level ML role, and broad skill requirements create high applicant competition.
Core ML engineering skills are transferable across industries but domain experience adds moderate sensitivity.
Explicit five-year Senior II requirement and ML domain experience requirement cause moderate screening.
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Translate business requirements into machine learning problem statements and lead cross-functional teams to develop machine learning models.
Evaluate, optimize, test, deploy, and monitor machine learning models ensuring performance, scalability, and efficiency.
Document models and collaborate with product teams to improve user experience through ML solutions.
Bachelor's degree in data science, applied mathematics, computer science or a related research-based field; Master’s or PhD preferred.
Minimum 5 years of relevant machine learning work experience (Senior II level).
Strong programming skills and experience with machine learning algorithms and model evaluation metrics.
Fluency in English and solid statistical, mathematical, analytical, and numerical skills.
Experienced in leading machine learning projects involving cross-functional collaboration with data scientists, developers, and business teams.
Able to convert complex business problems into production-level machine learning solutions and monitor their deployment.
Skilled in optimizing ML models for real-world application scenarios with a focus on performance and scalability.