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Staff/Principal Machine Learning Engineer - USA
Summary by AIEngineer.careers
Staff/Principal Machine Learning Engineer - USA is a Machine Learning Engineer role (full-time). with Inworld AI. in MOUNTAIN VIEW, US. Compensation shown: $240K–$385K. Imported listing (source: mechanic.jobserve.com). Apply on the employer's site (mechanic.jobserve.com).
Imported listing (source: mechanic.jobserve.com) · Apply on mechanic.jobserve.com
MOUNTAIN VIEW · US
$240K–$385K
Full-time
STAFF
The sections below reproduce the third-party job description for reference. AIEngineer.careers does not write or control this text.
Imported job description
Sourced from mechanic.jobserve.com
Inworld AI is seeking Staff and Principal level Machine Learning Engineers with deep NLP expertise to build generative AI products powered by large language models. You will experiment with cutting-edge ML techniques and develop production-grade scalable generative models for next-generation AI characters. The role is based in Mountain View, CA, with remote options available within the United States.
Responsibilities
- Explore and experiment with cutting edge ML techniques for applied NLP
- Develop and test production-grade scalable generative machine learning models
- Collaborate with cross-functional teams to integrate AI models into game experiences
Requirements
- 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
- Deep knowledge of machine learning frameworks such as PyTorch, TensorFlow, or JAX
Nice to Have
- 1+ years of experience training LLMs (6B parameters and larger) such as NeoX, LLaMA, PaLM, etc.
Inworld AI
Mountain View · US · 85+ employees
Inworld AI is a product-oriented realtime AI research lab and model provider focused on voice AI for natural, human-like conversation. Its platform supports interactive voice agents and conversational applications across areas such as entertainment, education, customer support, and enterprise use.
