Mid-Career Machine Learning Engineer, PlayStation

• Do you want to join a Machine Learning team committed to personalizing the PlayStation experience for hundreds of millions of users
• We are looking for someone who can build delightful products and experiences for millions, in an agile environment, collaborating with teams-across Engineering and Product
• Masters degree in CS/Statistics/Data Science, with a specialization in machine learning or equivalent experience
• Experience with Python, and ideally also Scala or Java
• Experience in developing ML models for structured data, and ideally also unstructured data
• Industry work experience in designing and implementing large-scale machine learning-based solutions that ideally include: recommender systems, personalization, and A/B testing
• Strong machine learning, and statistical knowledge

Desirable

• The work we do delivers impactful insights to build an increasingly dynamic and interactive experience
• The Machine Learning Engineers within the platform engineering group will deliver optimized interactions across PlayStation experiences and systems by designing, coding, training, documenting, cost-effectively deploying and evaluating very large-scale machine learning systems
• You will be immersed in groundbreaking ML technologies, tools and processes, as you help to advance our technical objectives and architectural initiatives
• Design and develop various machine learning and deep learning models and systems for high-impact consumer-facing applications such as content personalizations and product recommendations
• Work with a broad spectrum of state-of-the-art machine learning and deep learning technologies, in the areas of recommendation systems
• Create metrics and configure A/B testing to evaluate model performance offline and online to inform and convey our impacts to diverse groups of stakeholders
• Collaborate with cross-functional teams of technical members and non-technical members in architecture, design and code reviews
• Analyze and produce insights from a large amount of dynamic structured and unstructured data using modern big data and streaming technologies
• Produce reusable code according to standard methodologies in Python