PICO system prototyping team is looking to incubate the next generation XR products including MR headsets, AR glasses and more smart wearables, and is seeking talented individuals to develop and prototype novel LLM-powered applications and experiences for these products.
Requirements
- Solid understanding of fundamental Machine Learning, Deep Learning, and Natural Language Processing concepts.
- Hands-on experience with ML/DL frameworks (e.g., PyTorch, TensorFlow, Hugging Face Transformers) through coursework, research, or internships.
- Proficiency in at least one programming language, such as Python or C++.
- Deep understanding of Transformer architectures and attention mechanisms.
- Hands-on experience with LLM application development techniques such as Retrieval-Augmented Generation (RAG), function calling, and building AI agents.
- Experience in fine-tuning and evaluating Large Language Models (e.g., instruction tuning, RLHF).
- Familiarity with vector databases (e.g., Pinecone, Chroma) and prompt engineering best practices.
Responsibilities
- Develop and prototype novel LLM-powered applications and experiences for next-generation smart wearables, bringing the power of generative AI to everyday interactions.
- Contribute to the design and implementation of conversational agents, multimodal reasoning systems, and other LLM-driven features for our product concepts.
- Fine-tune, and evaluate Large Language Models for on-device and cloud-based deployments, with a focus on enhancing capabilities like reasoning, instruction following, and safety.
- Design and build application frameworks using modern LLM development patterns, such as Retrieval-Augmented Generation (RAG), function calling, and agentic workflows.
- Leverage and adapt state-of-the-art open-source LLMs (e.g., Llama, Mistral) and foundation models to fit the unique constraints and opportunities of smart glasses and AR.
- Design and implement robust evaluation frameworks to assess model performance, safety, and helpfulness, using both automated metrics and human-in-the-loop systems.
- Stay at the forefront of generative AI research, with a focus on prompt engineering, agent-based systems, and efficient LLM inference techniques.
Other
- Currently pursuing or recently graduated with a PhD degree in Computer Science, Electrical Engineering, or a related technical field.
- Successful candidates must be able to commit to an onboarding date by end of year 2026.
- Please state your availability and graduation date clearly in your resume.
- Applications will be reviewed on a rolling basis - we encourage you to apply early.
