Machine Learning Engineer II, Trust & Safety

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 Group Corporation.

Mid Level Machine Learning Engineer - Trust and Safety

San Mateo, CA

Do you want to join a Machine Learning team committed to making PlayStation the safest place to play? 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 ranging from predictive safety, content personalizations, search, virtual assistant, time series forecasting and more.
• Work with a broad spectrum of state of the art machine learning and deep learning technologies, in the areas of various machine learning problems such as multilingual text classification, language modeling  and multi-modal learning.
• Analyze and produce insights from a large amount of dynamic structured and unstructured data using modern big data and streaming technologies
• 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.
• Produce reusable code according to standard methodologies in Python, Scala or Java
• Collaborate with cross-functional teams of technical members and non-technical members in architecture, design and code reviews.

You Bring:

• Masters degree in CS/Statistics/Data Science, with a specialization in machine learning or equivalent technical degree with experience.
• 3–6 years experience in applied machine learning or related fields.
• Knowledge of responsible AI principles (fairness, explainability, bias mitigation).
• Experience with Python or Scala or Java.
• Experience in developing production-level large-scale ML models and data pipelines.
• Industry work experience in designing and implementing machine learning-based solutions that ideally include: online safety, voice-activated conversational systems, recommender systems, search engines, personalization, time series forecasting, and A/B testing.
• Strong machine learning, statistical and analytical skills.

Preferred Qualifications:

• Prior work in Trust & Safety, security, fraud detection, or adversarial ML.
• Experience with Spark, Kubernetes, Jenkins, Prometheus.
• Proficient with Machine learning frameworks such as Tensorflow, PyTorch, MLlib.
• Familiarity with standard methodologies in large-scale Deep Learning training/Inference.
• Experience in cloud-based environments, such as AWS.
• Experience working with custom ML platforms.

 

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At SIE, we consider several factors when setting each role’s base pay range, including the competitive benchmarking data for the market and geographic location.

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<