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Strong employer brand, metro location, mid-level ML role, and broad technical requirements increase competition.
Recommender-system and production ML skills are moderately transferable across industries.
Explicit 3+ years, mandatory recommender/production ML, big-data and cloud skills enforce strict filters.
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Design, develop, and deploy large-scale recommendation systems and machine learning models for personalized lock screen and live entertainment experiences.
Own data preparation, model training, evaluation, deployment pipelines, and monitor model performance to identify improvements.
Collaborate cross-functionally with Product, Engineering, UX, and Business teams to integrate ML and GenAI-driven features and contribute to thought leadership.
Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Electrical Engineering, Operations Research, Economics, Analytics, or related fields; PhD is a plus.
Minimum 3 years of industry experience in ML/Data Science, preferably with large-scale recommendation systems or personalization.
Proficiency in Python and ML frameworks (PyTorch/TensorFlow) and experience with big data tools (Spark, Hadoop) and cloud platforms (Azure, AWS, GCP/Vertex AI).
Experience with algorithms in NLP, Reinforcement Learning, Time Series, Deep Learning; familiarity with ML system deployment and data processing at scale.
Experienced in building and scaling recommendation and personalization ML systems with measurable production impact.
Strong technical expertise in classical ML, deep learning, and emerging generative or agentic AI workflows.
Comfortable working in cross-functional teams, balancing technical rigor with product/business priorities, and contributing to external/internal knowledge sharing.