Senior Machine Learning Engineer

Requisition Number: 172290

Position Title: Software Engineer III

External Description:

#WeAreEA and we exist to inspire the world to play. EA values creativity, pioneering, passion, determination, learning, and teamwork. We mean things like acting with curiosity, speaking up with original ideas, and committing to each other as one team. We're looking for all the best kinds of people to make great experiences for our players. People want a job that inspires them, while giving them room to enjoy their lives. And we want to give them that. We celebrate diversity and inclusion by creating a place where you can come to work and be yourself.

The Positive Play Group at Electronic Arts is changing the game for good. Our goal is to reimagine and rebuild the gaming experience to be an inclusive, fair and positive one for all players. We are part of the Experience organization, and you will report to the Director of Player Connection to help build a first-of-its-kind foundational technology to power the social ecosystem in and around our games, by enabling meaningful connections between our players, our games and our content.

Come join us! We're hiring an ML Engineer to join EA's Positive Play team.

The Opportunity Ahead: The Machine Learning Engineer will help us define and build the next generation of infrastructure to connect our players more meaningfully. Our mission is to enable teams at EA to meaningfully connect people with other players, content and experiences, based upon data sets with a multitude of data points. In this role you will work closely with cross-discipline peers on the Social Accelerator team to develop and deploy machine learning solutions to bring this mission to life.

Responsibilities/Skills:

Use your expertise in Machine Learning to help create healthier short- and long-term behaviors through:

• Oversee and guide the design, development, and evolution of our Social Accelerator ML models
• Develop highly scalable models and tools leveraging machine learning and recommender systems
• Coordinate with Product leadership to identify both the long-term and short-term needs of the Social Accelerator
• Identify and collect features, data and other requirements and create effective roadmaps
• Code deliverables in tandem with the engineering team
• Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU)

Qualifications:

• Experience working in a product and data-driven environment (Python, Scala, Java, SQL, or C++, with Python experience required)
• Experience with modern machine learning frameworks such as tensorflow, pytorch and keras.
• Understand storage solutions and when to use them (e.g. Graph Database, Cassandra, Relational database)
• You have a broad ML background, including familiarity with Graph ML and various recommender systems
• You have experience in the entire machine learning production cycle, ranging from architecting data pipelines and being self-sufficient in collecting data, over the design and implementation of models to the offline and online evaluation the performance of models
• An interest in fair and explainable machine learning and willingness to go beyond black-box solutions
• Academic and/or proven experience in knowledge graphs, data management, natural language processing.
• Have excellent communication skills and the ability to translate business intuition into data-driven hypotheses that result in impactful engineering solutions.

Join us in driving the next revolution in games.

City:

State:

Community / Marketing Title: Senior Machine Learning Engineer

Company Profile:

Electronic Arts Inc. 是全球领先的互动娱乐软件公司。 EA 提供适用于联网主机、个人电脑、手机和平板电脑的游戏、内容和在线服务。

EEOText: EA 是一个奉行机会均等的雇主。 所有招聘决定均不考虑种族、肤色、国籍、血统、生理性别、社会性别、性别认同或表达、性向、年龄、遗传信息、宗教信仰、残障状况、医疗状况、怀孕状况、婚姻状况、家庭状况、退伍军人身份或其他任何受法律保护的特征等因素的影响。 我们也会遵照相关法律，考虑雇佣带犯罪记录的合格申请者。 EA 还会遵照相关法律，为符合条件的残障个体改善工作环境。

Days Open: 125

Can this position be remote?: 1

EEO Employer Verbiage:

EA 是一个奉行机会均等的雇主。 所有招聘决定均不考虑种族、肤色、国籍、血统、生理性别、社会性别、性别认同或表达、性向、年龄、遗传信息、宗教信仰、残障状况、医疗状况、怀孕状况、婚姻状况、家庭状况或退伍军人身份等因素的影响。 EA 还会遵照相关法律，为符合条件的残障个体改善工作环境。