Senior Machine Learning Engineer, Recommendation Systems
PlayStation GlobalAbout the role
Why PlayStation?
PlayStation isn’t just the Best Place to Play — it’s also the Best Place to Work. Today, we’re recognized as a global leader in entertainment producing The PlayStation family of products and services including PlayStation®5, PlayStation®4, PlayStation®VR, PlayStation®Plus, acclaimed PlayStation software titles from PlayStation Studios, and more.
PlayStation also strives to create an inclusive environment that empowers employees and embraces diversity. We welcome and encourage everyone who has a passion and curiosity for innovation, technology, and play to explore our open positions and join our growing global team.
The PlayStation brand falls under Sony Interactive Entertainment, a wholly-owned subsidiary of Sony Corporation.
Senior Machine Learning Engineer, Recommendation Systems
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 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
- 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
- Experience working with stakeholders, owning projects, translating requirements, defining milestones, and mentoring junior members
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Please note that the base pay range may vary in line with our hybrid working policy and individual base pay will be determined based on job-related factors which may include knowledge, skills, experience, and location.
In addition, this role is eligible for SIE’s top-tier benefits package that includes medical, dental, vision, matching 401(k), paid time off, wellness program and coveted employee discounts for Sony products. This role also may be eligible for a bonus package. Click Apply for this role