Researcher - Efficient Architecture LLMs

💰 ₹50,400 - ₹80,640 (Est.) 📍 Montréal

Job Description

Position: Researcher - Efficient Architecture for LLMs
Location: Montreal

Job description

Huawei Canada has an immediate 12-month contract opening for a Researcher.

About the team:

Founded in 2012, the Noah’s Ark lab has evolved into a prominent research organization with notable achievements in academia and industry. The lab’s mission focuses on advancing artificial intelligence and related fields to benefit the company and society. Driven by impactful, long-term projects, the aim is to enhance state-of-the-art research while integrating innovations into the company's products and services, including LLMs, RL, NLP, computer vision, AI theory, and Autonomous driving.

About the job:
• Propose and develop novel research ideas to advance the state of the art in large language models (LLMs).
• Participate in applied research projects focused on enabling long-context LLMs, including work on efficient architectures, data curation, and post-training methods.
• Deliver end-to-end projects by designing and executing experiments, analyzing results, and presenting findings.
• Publish research in top-tier machine learning and natural language processing (NLP) conferences.
• Supervise and mentor a small group of researchers and engineers to deliver projects and publish conference papers.
• Track advances across the LLM and AI ecosystem, translating new developments into actionable insights for the team.

Job requirements

About the ideal candidate:
• A Ph.D. in Computer Science, Software Engineering, or a related field.
• First-author publications in top-tier machine learning (ML) and natural language processing (NLP) venues such as NeurIPS, ICML, ICLR, ACL, EMNLP, or NAACL.
• A deep understanding of NLP and large language model (LLM) fundamentals and state-of-the-art methods, coupled with a strong theoretical grounding in machine learning.
• Expertise in modern LLM architectures, including transformer models (e.g., Llama, Qwen) and linear-attention models (e.g., Mamba, GLA).
• Strong programming skills in Python with expertise in PyTorch.
• Experience with modern LLM training and inference stacks (e.g., Hugging Face Transformers/Accelerate, Megatron-LM, vLLM).
• Excellent oral and written communication skills.

Huawei aims to support a French-speaking work environment for its employees in Quebec. We have taken steps to avoid requiring a language other than French for this position. However, proficiency in English is essential for this role for the following reasons:

The person will be required to communicate regularly with colleagues located outside Quebec, where English is the primary language used for communication between offices. In addition, the nature of the tasks related to this position, which falls within a highly specialized field of artificial intelligence, also requires knowledge of English.

💡 Quick Summary

Seeking a career-building opportunity? The Researcher - Efficient Architecture LLMs position is now open for candidates interested in the Architect / Interior Designer Jobs sector. This role in Montréal offers a professional environment and growth potential.

Requirement Snapshot: Candidates should possess basic communication skills, a proactive attitude, and the ability to work in a team. Experience in Architect / Interior Designer Jobs is a plus.

Sponsored

Job Details

Company Name: Huawei Technologies Canada Co., Ltd.

Frequently Asked Questions

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The expected salary for Researcher - Efficient Architecture LLMs in Montréal is ₹50,400 - ₹80,640 (Est.) per month. Actual compensation may vary based on experience and negotiation.
No, Researcher - Efficient Architecture LLMs is an on-site position based in Montréal. Candidates must be able to commute or relocate to this location.
Basic communication skills, a proactive attitude, and the ability to work in a team are required for Researcher - Efficient Architecture LLMs. Previous experience in Architect / Interior Designer Jobs is a plus. Freshers may also apply depending on the employer's requirements.
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