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Machine Learning Engineer II

Playstation

Summary

The job is for a Machine Learning Engineer II position at PlayStation in San Diego, CA. The engineer will work on personalizing the PlayStation experience for users by designing, coding, training, deploying, and evaluating large-scale machine learning systems. The engineer will collaborate with cross-functional teams and work with state-of-the-art machine learning and deep learning technologies. The ideal candidate should have a Master's degree in CS/Statistics/Data Science, experience in developing large-scale ML models and data pipelines, and industry work experience in designing and implementing machine learning-based solutions. The estimated base pay range for this role is $129,000—$193,400 USD. Sony is an Equal Opportunity Employer.

Job description

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.

Machine Learning Engineer II

San Diego, 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 ranging from content personalizations, search, information extraction to online safety, 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 recommendation systems, natural language processing (e.g. transformer, RNN, BERT), reinforcement learning, time series forecasting.
  • 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, Scala or Java

You Bring:

  • Masters degree in CS/Statistics/Data Science, with a specialization in machine learning or equivalent experience.
  • Experience with Python, and Scala or Java
  • Experience in developing large-scale ML models and data pipelines.
  • Industry work experience in designing and implementing machine learning-based solutions that ideally include: voice-activated conversational systems, recommender systems, search engines, personalization, time series forecasting, and A/B testing.
  • Strong machine learning, statistical knowledge

Preferred Qualifications:

  • Experience with audio data manipulation and signal processing
  • Experience with Spark, Kubernetes, Jenkins, Prometheus.
  • Proficient with Machine learning frameworks such as Tensorflow, PyTorch, MLlib.
  • Familiarity with standard methodologies in large-scale DL training/Inference.
  • Experience in cloud-based environments, such as AWS.
  • Experience working with custom ML platforms.
  • Experience in building and maintaining online customer-facing microservices

 

#LI-KSI

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 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 here to learn more.

The estimated base pay range for this role is listed below.
$129,000—$193,400 USD

Equal Opportunity Statement:

Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy or maternity, trade union membership or membership in any other legally protected category.

We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond.

PlayStation is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.

Location: United States, San Diego, CA

Country: United States

Date found: 2023-03-17

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