Why Join Inworld

Inworld is the best-funded startup in AI and gaming, with a $500 million valuation and backing from top-tier investors like Intel, Microsoft, Lightspeed, Bitkraft, Founders Fund, Kleiner Perkins, and more. Inworld was recognized by CB Insights list of the 100 most promising AI companies in the world. We’ve also been nominated alongside Anthropic, DeepMind, OpenAI and Nvidia for the Generative AI Innovator of the Year at the VentureBeat Awards 2023, and are under consideration to be a Gartner Cool Vendor in 2023.

Inworld is the leading character engine for creating AI NPCs in games and immersive entertainment. Inworld powers NPCs in experiences built by Niantic, NetEase Games, LG, Alpine Electronics, the Disney Accelerator, and more. We go beyond large language models (LLMs) to add multimodal orchestration of personality and contextual awareness that renders NPCs within the lore and logic of their worlds. 

Inworld is well positioned to take a long-term view when it comes to supporting the developer community today, and stay ahead of the curve in the ever-evolving landscape of generative AI for tomorrow. By joining us now, you’ll be stepping into a role where your ideas and efforts will directly influence our path forward, making this moment an extraordinary one to become a key player in our journey of shaping the future of AI and gaming.

We are seeking Staff and Principal level Machine Learning Engineers with extensive experience in Natural Language Processing (NLP). You will be at the forefront of building generative AI products that utilize Large Language Models (LLMs) to create next-generation AI characters.

Qualifications

• BA/BS degree or higher in Computer Science, Engineering, or a similar technical field.

• 6 years of experience with software development in one or more programming languages. 

• 4 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. is considered a plus.

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

Responsibilities

• Explore and experiment with cutting edge ML techniques for applied NLP.

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

In-office location: Vancouver, Canada.

Remote location: Canada.