Join the Battlefield Long Range Technology team at Electronic Arts, where we are dedicated to pushing the boundaries of gaming technology. As a Machine Learning Engineer with Battlefield Studios, you'll play a pivotal role in revolutionizing the gaming experience. Your expertise in cutting-edge machine learning techniques will be crucial in implementing ML components that directly enable key game features. Additionally, you will utilize GenAI technology to significantly boost game development efficiency, ensuring our players enjoy unparalleled gaming experiences. If you're passionate about merging technology with creativity, we invite you to be part of our journey to redefine the future of gaming.Responsibilities:● Research, design and implement AI and machine learning solutions to solve challenging problems from our game development lifecycle.● Apply current and emerging techniques in deep learning (DL), natural language processing (LLM and other NLP technologies) and other machine learning areas to improve existing tools and workflows.● Prototyping ideas to demonstrate how ML and AI technologies can be applied to game features and designs.● Prepare and manage datasets needed for AI and Machine Learning R&D work.● Work in partnership with other EA game teams, centralized research teams, and centralized platform teams to integrate AI solutions into Battlefield.● Document and present findings and solutions to non-technical audiences, and technical audiences that are not ML/AI experts.● Support and manage ML products and pipelines, as well as integration.Required qualifications and skillsets:● Bachelor or Master (Preferred) Degree in Computer Science, Machine Learning, Engineering, or related field.● Minimum 3+ years of experience as Machine Learning Engineer, AI Engineer, Algorithm Engineer, Data Scientist, or equivalent.● Hands-on expertise in building deep learning solutions with popular ML frameworks (Tensorflow, Keras, Pytorch, Jax, etc.)● Hands-on experience in building ML/AI solutions around LLM or VLM. Familiarity with RAG, LangChain, MCP, or Haystack.● Experience with Agentic AI-related frameworks and tools (MCP, A2A, n8n, LangGraph, ADK, etc.).● Experience in Reinforcement Learning (RL) R&D and framework development.● Experience with RL for either Bots or RLHF.● Experience with ML/AI development using AWS, Azure, or GCP products and services.● Experience with handling docker containers, Kubernetes, etc.● Experience with CI/CD pipelines.● Experience or basic knowledge of API development for LLM solutions.● Experience or basic knowledge of game engines and ML model deployment into game engines.
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