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RESPONSIBILITIES:
• You will be involved in directly driving application of machine learning and AI to solve various product and business problems including ML model lifecycle management with ideation, experimentation, implementation, and maintenance.
• Your responsibilities will include enabling the team in moving forward with ML/AI solutions to optimise various components across our music streaming platforms.
• Your work would be impacting millions of users the way they consume music and podcasts, it would involve solving cold start problems, understanding user personas, optimising ranking and improving recommendations for serving relevant content to users.
• We are looking for a seasoned engineer to orchestrate our recommendations and discovery projects and also be involved in tech management within the team.
• The team of talented, passionate people in which you’ll work will include ML engineers and data scientists.
• You’ll be reporting directly to the head of the engineering and will be
instrumental in discussing and explaining the progress to top management and other stake holders.
• You’ll be expected to have regular conversations with product leads and other engineering leads to understand the requirements, and also similar and more frequent conversation with your own team.
REQUIREMENTS:
• A machine learning software engineer with a passion for working on exciting, user impacting product and business problems
• Stay updated with latest research in machine learning esp. recommender systems and audio signals
• Have taken scalable ML services to production, maintained and managed their lifecycle
• Good understanding of foundational mathematics associated with machine learning such as statistics, linear algebra, optimization, probabilistic models
Minimum Qualifications
• 13+ years of industry experience doing applied machine learning
• 5+ years of experience in tech team management
• Fluent in one or more object oriented languages like Python, C++, Java
• Knowledgeable about core CS concepts such as common data structures an algorithms
• Comfortable conducting design and code reviews
• Comfortable in formalising a product or business problem as a ML problem
• Master’s or PhD degree in Computer Science, Mathematics or related field
• Industry experience with large scale recommendation and ranking systems
• Experience in managing team of 10-15 engineers
• Hands on experience with Spark, Hive, Flask, Tensorflow, XGBoost, Airflow
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