Job Title: Gameplay Data Science Engineer

Location: Hybrid - Vancouver or Los Angeles

Reports to: Technical Director

Job Summary:

Founded in 2010, Respawn was created with the philosophy that when talented people have creative freedom, they’ll make extraordinary games that achieve the unexpected. Respawn Entertainment is the Academy Award-winning studio behind Apex Legends, Titanfall, and Star Wars Jedi titles. Join us to help shape the future of one of the world’s leading live service franchises: Apex Legends.

As a Gameplay & Data Science Engineer, you will drive the Research & Development of advanced bot behaviors and AI frameworks to enhance the Apex Legends experience. You will work at the intersection of data science and gameplay programming, utilizing machine learning and reinforcement learning to create intelligent agents. Working closely with gameplay teams, game designers, and producers, you will implement robust AI systems that improve game quality and player engagement. Your work will ensure our AI is of outstanding quality and provides the best experience for our players.

Responsibilities:

• Lead R&D efforts for game bots using machine learning, reinforcement learning, and neural networks to create realistic agent behaviors.

• Design, implement, and maintain gameplay-focused AI frameworks, including Utility AI systems, directly within the game engine.

• Collaborate with gameplay teams and designers to translate creative vision into technical specifications and scalable AI solutions.

• Develop and program algorithms to structure and analyze gameplay data to improve bot performance and decision-making.

• Optimize AI systems and data pipelines to ensure high performance and stability across consoles and dedicated servers.

Required Qualifications:

• 5+ years of experience in data science, machine learning engineering, or gameplay programming within the games industry.

• Strong proficiency in C/C++ and Python for both engine-level implementation and algorithmic development.

• Hands-on experience with reinforcement learning, supervised/unsupervised learning, and AI architectures like Utility AI.

• Experience with large-scale computing frameworks, big-data techniques, and building scalable data pipelines.

• Solid foundation in mathematics, statistics, and optimization theory applied to game AI and machine learning.

• Bachelor's or advanced degree in Computer Science, Data Science, Engineering, or equivalent practical experience.