Machine Learning Engineer
With multiple awards to our name, Larian Studios has proven that we’re dedicated to delivering high-quality role-playing games As we move on to new projects, the studio that brought you Baldur’s Gate 3 & Divinity: Original Sin 2 is looking for a Machine Learning Engineer to join the team and help us in crafting the high calibre games our fans have come to expect.
Explore opportunities for the application of ML techniques to optimize and improve our game engine, game creation pipelines, and ultimately enhance the player experience
Maintain and improve the current ML systems that are critical to our development pipelines
Educate all developers across the global studio in the domain and application of ML and associated technologies
Generate, gather and build a knowledge base of research and expertise in the domain and application of ML
At least 4 years of experience in Machine Learning Engineering
Proficient in python
Degree in a technical field such as Machine Learning, Computer Science, Mathematics, or equivalent practical experience
Passionate about AI, ML, and computational statistics
Open minded, willing to experiment, collaborate and iterate within a technical domain
Good written and spoken English
Enjoy coaching and mentoring
This is a full-time, on-site role, requiring your presence in the office to support collaboration and creativity
Experience in the gaming industry
Proficient in C++
Experience in ML Ops (docker, K8s) and Reinforcement Learning
An international team of over 500 employees spread across 7 studios around the world, each of which have their own unique qualities, and maintain a small-studio feel
An open, collaborative environment where ideas are welcome and encouraged
A managerial team consisting of highly experienced game developers at the top of their fields
Sharing hobbies and passions with like-minded colleagues
Inclusive environment with many activities organized by the studios or the employees
Commitment to making the best game possible for the fans, including listening to community feedback
