Mid-Career Machine Learning Engineer - Recommendation Systems

Machine Learning Engineer II

San Francisco, CA

Do you want to join a Machine Learning team committed to personalizing the PlayStation experience for hundreds of millions of users? 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.

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. Further, you will be immersed in groundbreaking ML technologies, tools and processes, as you help to advance our technical objectives and architectural initiatives.

You Will:

• 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

You Bring:

• 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

Preferred Qualifications:

• Proficient with Machine learning frameworks such as Tensorflow, PyTorch, MLlib
• Experience with Databricks, Spark, Tecton, Kubernetes, Helm, Jenkins
• Familiarity with standard methodologies in large-scale DL training/Inference
• Experience with reducing model serving latency, memory footprint
• Experience in cloud-based environments, such as AWS
• Experience working with custom ML platforms

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