Intern Researcher – LLM Agents – Huawei – Markham, ON

Company: Huawei

Location: Markham, ON

Job description: Our team has an immediate 12-month Internship opening for a Researcher.


  • Research and develop innovative models of LLM agents (decision-making, planning, reasoning, etc) with applications on open-world virtual environments.
  • Publish at top-tier ML conferences, file high-value patents, and write scientific technical reports.
  • Contribute to the design, implementation, test, and maintenance of research and development frameworks.
  • Ability to learn and grow in a collaborative research and development environment; communicate and develop solutions for complex learning problems.
  • Keeping up-to-date on selected areas of ML (such as Transformers, State Space Models, and deep learning) and new advances in the NLP/AI field and bringing insights to the team.

What you’ll bring to the team:

  • Ph.D. in Computer Science, Electrical and Computer Engineering, Statistics, Applied Mathematics or a related technical field (or Master’s with related research experience and publications) with 2+ years of research and development experience.
  • Good theoretical knowledge and methodological experience in the deep learning research-and-development cycle: literature review, model formulation and development, training, testing, monitoring, fine-tuning, and quantitative/qualitative analysis.
  • Proficiency in a programming language (e.g. Python); Good understanding of basic data structures and computational algorithms; strong AI/ML coding skills; experienced in deep learning/machine learning frameworks (PyTorch and Tensorflow).
  • Excellent team working, technical writing and presentation, analytical and problem-solving skills.
  • Experience with LLMs, Transformer pipelines, and training and evaluation algorithms in NLP; related frameworks (Huggingface, DeepSpeed, PEFT).
  • Good knowledge and experiences with various learning paradigms such as in-context learning, prompt tuning, and parameter efficient fine-tuning.
  • Publication record at top-tier ML/AI conferences such as NeurIPS, ICML, ICLR, etc.

Immediate 12-month internship opening for a Researcher to research and develop innovative models of LLM agents for open-world virtual environments. Responsibilities include publishing at top-tier ML conferences, contributing to research frameworks, learning and growing in a collaborative environment, and keeping up-to-date on ML advances. Requirements include a Ph.D. in a related field or a Master’s with research experience, proficiency in programming languages, experience with deep learning frameworks, and knowledge of NLP/AI. Additionally, strong team working, technical writing, presentation, analytical, and problem-solving skills are needed. Experience with LLMs, Transformer pipelines, NLP frameworks, various learning paradigms, and publication record at top-tier conferences is also required.
Job Description:

We are looking for a highly motivated and detail-oriented candidate to fill the position of Administrative Assistant. The successful candidate will be responsible for providing administrative support to a busy office environment. This will include tasks such as managing calendars, scheduling appointments, answering phones, and maintaining office supplies. The ideal candidate will have excellent communication skills, strong organizational abilities, and an ability to work well under pressure. Previous experience in an administrative role is preferred.

– Manage calendars and schedule appointments
– Answer phones and direct calls to appropriate parties
– Maintain office supplies and inventory
– Assist with special projects as needed

– High school diploma or equivalent
– Previous experience in an administrative role preferred
– Excellent communication skills
– Strong organizational abilities
– Ability to work well under pressure

If you meet the qualifications and are looking for a challenging and rewarding career opportunity, we encourage you to apply today.

Expected salary:

Job date: Sun, 18 Feb 2024 02:14:58 GMT