Electronic Arts

We’re EA—the world’s largest video game publisher. You’re probably familiar with many of our titles—Madden, FC, Apex Legends, The Sims, Need for Speed, Dead Space, Battlefield and Star Wars, to name a few. But maybe you don’t know how we’re committed to creating games for every platform—from social to mobile to console —to give our players that anytime, anywhere access they demand. What does that mean for you? It means more opportunities to unleash your computing genius. 

EA’s Digital Platform (EADP) organization is responsible for driving critical technology decisions and investments for EA on a global scale, across all divisions and studio teams. Technology and engineering leadership at EA is critical to making the industry’s best games & services and the EADP team is leading the way to providing cross-platform services that will keep our consumers connected with our games anytime, anywhere with anyone.

Join EA Hyderabad as a Data Scientist II and become a key player in our central engineering team. You'll have the exciting responsibility of developing custom machine learning models to tackle real-world challenges within EA's games. EA’s network of games caters to tens of millions of monthly active users. You'll have the opportunity to build solutions that can scale at real time to handle several thousand requests per second and driving the player engagement of many of the industry’s most popular titles.  If you like solving complex computing problems, are a passionate team player and thrive in a fast paced, ever changing development environment this is a great opportunity for you. 

What Would You Do

• Develop and implement custom machine learning models for text and image classification.
• Clean, preprocess, and analyze large datasets, ensuring data quality and integrity.
•  Address and manage imbalanced datasets to optimize model performance.
•  Deploy and host machine learning models, ensuring their scalability and reliability in production environments.
•  Monitor and maintain models in production, implementing feedback loops for continuous improvement.
•  Identify and mitigate biases in models to ensure fairness and accuracy.
•  Collaborate with cross-functional teams to understand business needs and translate them into technical requirements.
•  Document processes and model performance, providing insights and recommendations.

Must have Skills

• Bachelor of Technology or Engineering from a reputed institute
• Bachelor’s or master’s degree in computer science, Data Science, Statistics, or a related field.
•  3-5 years of experience in building and deploying machine learning models.
•  Proficiency in Python or R, with experience in libraries such as TensorFlow, PyTorch, or Scikit-learn.
•  Strong understanding of data preprocessing techniques and handling imbalanced datasets.
•  Experience in deploying models using cloud platforms (AWS, GCP, or Azure).
•  Knowledge of model evaluation metrics and techniques to identify and reduce bias.
•  Excellent problem-solving skills and attention to detail.
•  Strong communication skills, with the ability to explain complex concepts to non-technical stakeholders.
•  Good understanding of LLM architecture, fine-tuning, and training LLMs.
•  Robust understanding of AI agents.
• Superb ability to take high level direction, work through ambiguity and drive to execution in an iterative model.
• Superb ability to translate business requirements into technical design & architecture.
• Ability to communicate ideas clearly and effectively.

Highly Desired Skills

• Practical experience with deep learning architectures (e.g., Transformers, CNNs, RNNs/LSTMs) and applying them effectively in NLP and computer vision projects.
• Strong understanding of data preprocessing techniques and handling imbalanced datasets.
• Familiarity with MLOps practices and tools.
• Experience with containerization (Docker) and orchestration (Kubernetes).