Researcher - Machine Learning

Huawei Technologies Canada Co., Ltd.; Markham; On-site; CAD 80,000 - 120,000; Full time

Job summary

A leading research organization in Canada is seeking a researcher for a 12-month contract. The role involves participating in cutting-edge AI projects, implementing algorithms, and collaborating with a talented team. Ideal candidates should have advanced degrees in Computer Science and strong knowledge of Deep Learning and reinforcement learning. Proficiency in Python and experience with machine learning frameworks are essential.

Qualifications

• Strong knowledge of Deep Learning components and architectures.
• Practical experience in reinforcement learning.

Responsibilities

• Participate in innovative research projects on LLM reasoning.
• Implement algorithms and deploy them into internal products.

Skills

Deep Learning

Reinforcement Learning

Communication

Education

Master’s or PhD in Computer Science

Tools

Python

TensorFlow

PyTorch

Job description

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Huawei Canada Researcher Position - 12-Month Contract

About the team:

Founded in 2012, Noah’s Ark lab has become a prominent research organization with achievements in academia and industry. The lab focuses on advancing artificial intelligence and related fields to benefit society and the company. Its projects aim to enhance state-of-the-art research and integrate innovations into products and services, including LLMs, RL, NLP, computer vision, AI theory, and autonomous driving.

About the job:

1. Participate in innovative research projects on LLM reasoning and AI agents;
2. Implement algorithms for proposed models and applications, and deploy them into internal products;
3. Collaborate closely with team researchers;
4. Stay updated on ML research areas and contribute by writing scientific reports;
5. Provide insight reports on the latest literature work.

About the ideal candidate:

1. Master’s or PhD in Computer Science or related technical field;
2. Strong knowledge of Deep Learning components (training, regularization, generalization) and familiarity with architectures like Transformers, LSTMs, Diffusion Models;
3. Practical or research experience in reinforcement learning;
4. Experience applying machine learning models to real-world problems;
5. Proficiency in Python, with experience in TensorFlow or PyTorch;
6. Experience with parallel model training, RL training, DeepSpeed, and Large Language Models is a plus;
7. Excellent verbal and written communication skills.