Staff / Principal Machine Learning Engineer - USA

Staff / Principal Machine Learning Engineer - USA

Mountain View, California, United States Inworld is a leading provider of AI technology for real-time interactive experiences, backed by top-tier investors including Intel Capital, Microsoft’s M12 fund, Lightspeed Venture Partners, and others. We offer a comprehensive framework for building production-ready interactive experiences, supporting stages from design to ML pipeline optimization and custom infrastructure. Our solutions enable developers to bring AI engines in-house, optimized for real-time data ingestion, low latency, and large-scale deployment. Our clients include Ubisoft, NVIDIA, Niantic, NetEase Games, and LG, with partnerships with Microsoft Xbox, Epic Games, and Unity. Recognized as one of the 100 most promising AI companies in 2024 by CB Insights and among LinkedIn's Top Startups of 2024 in the USA, we are seeking experienced Staff and Principal Machine Learning Engineers. You will work on cutting-edge generative AI products and frameworks utilizing modern AI stacks, including LLMs and diffusion models. Qualifications

BA/BS or higher in Computer Science, Engineering, or a related field. At least 6 years of software development experience in languages like Python or C++. Minimum 4 years applying ML algorithms in NLP, speech processing, or action planning. Proficiency with ML frameworks such as PyTorch, TensorFlow, or JAX. Experience fine-tuning and evaluating LLMs like LLaMA, Mistral, or Qwen is a plus. Knowledge of embedded systems or ML on edge devices is a plus. Ideal Candidate Traits

Strong software engineering skills with a results-oriented approach. Excellent problem-solving and analytical abilities. Familiarity with AI tools like transformers, diffusion models, and reinforcement learning. Ability to collaborate effectively in a fast-paced environment. Passion for staying updated with ML research and applications. Responsibilities

Research and experiment with advanced ML models to enhance AI capabilities. Develop scalable infrastructure for training, evaluating, and deploying ML models. Mentor junior engineers and promote a collaborative learning environment. Representative Projects

Assessing the impact of attention algorithms within LLM infrastructure on quality and latency. Designing APIs for developers to create and deploy AI voices in real-time. Optimizing transformer-based speech recognition models for specific devices using on-device matrix multiplication backends. Location: Mountain View, CA. Candidates should be based in the SF Bay Area or willing to relocate, with on-site work a few days weekly. Salary range: $240,000 - $385,000, plus equity and benefits. Salary is determined by location, level, experience, and business needs. Range may change over time. Application materials: PDF, DOC, DOCX, TXT, RTF. Please include your LinkedIn profile, website, and answer the following: Are you legally authorized to work in the US? * Will you require sponsorship now or in the future? * Are you willing to work in the SF Bay Area? * When can you start? Additional questions: Describe your experience deploying Large Language Models in production. What challenges did you face and how did you overcome them? Provide an example of your involvement in ML research and experimentation, key findings, and impact on model design and performance. Discuss your experience optimizing model training and serving on GPUs or TPUs, including techniques to improve efficiency and reduce latency.

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