Why Join Inworld

Inworld is a developer platform for building AI characters. We go beyond large language models (LLMs) and add performance, configurable safety, knowledge, memory, narrative controls, multimodality, and more. We’re focused on enabling character-based interactions for immersive experiences like video games, brand activations, and training simulations. 

Inworld uses advanced AI to build generative characters whose personalities, thoughts, memories, and behaviors are designed to mimic the deeply social nature of human interaction. Our platform lets you create characters with personality and contextual awareness to keep them in-world and on brand. Integrations make it easy for developers to deploy characters into immersive experiences, while scale and performance are optimized for real-time experiences. 

Inworld AI is funded by top-tier investors, including Kleiner Perkins, Intel, Microsoft, and Founders Fund, and a team of all-star angels - corporate executives, top VC funds' partners, and industry veterans from Riot Games, Twitch, and Oculus.

We are seeking a Senior or higher-level Machine Learning Engineer with extensive experience working with generative large language models. You will be at the forefront of building generative AI products that utilize generative Large Language Models (LLMs) to create next-generation AI characters.

Qualifications

• Bachelor’s degree or equivalent practical experience.

• 5 years of experience with software development in one or more programming languages, or 3 years of experience with an advanced degree.

• 3 years of experience with applying machine learning algorithms in natural language processing domains.

• 1+ years of experience training or fine-tuning generative LLMs (6B parameters and larger) such as GPT3, PaLM, etc.

• Programming experience in Python. 

• Deep knowledge of machine learning frameworks such as PyTorch or JAX. 

• Experience with Triton is a big plus.

Responsibilities

• Explore artificial intelligence methods to support content creation, language understanding, etc. 

• Develop and test production-grade scalable generative machine learning models.

• Create and verify the latest research methods for controllable text and code generation.

• Develop and test data processing pipelines.