Senior Researcher, Explainable AI at Huawei Technologies Co. Ltd - Qatar

Helsinki, Uusimaa, Finland -

Full Time

Start Date

Immediate

Expiry Date

15 Jul, 26

Salary

0.0

Posted On

16 Apr, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Explainable AI, Deep Learning, Machine Learning, Large Language Models, Neural Networks, Computer Vision, Python, Java, C++, PyTorch, TensorFlow, AI Alignment, Model Robustness, Data Attribution, Content Safety

Industry

Telecommunications

Description

Huawei Consumer Business Group is the leader in the all-scenario AI life. It covers smartphones, PC and tablets, wearables, mobile broadband devices, family devices and device cloud services. Huawei Consumer Business Group is dedicated to delivering the latest technologies to consumers. We believe in creating safe, privacy-friendly, and high-quality products with great user experiences for our consumers. The mission of Cloud Content Security Lab at our Helsinki Research Center is to protect the online safety of Huawei mobile users within the Harmony OS ecosystem through technological advancements. We build advance AI detection solutions to ensure content safety, safety in AI such as agentic AI safety, machine unlearning. We are looking for a passionate and motivated researcher with a solid track record of solving challenging problems, advancing state-of-the-art, and demonstrated passion for ground-breaking research that could be scaled to production environment with an emphasis on the intersection of AI and Safety. This is a full‑time consultant position based in Ruoholahti, Helsinki, where you will be employed by a Huawei external supplier. Your responsibilities: · Create new techniques to make AI models more interpretable, unbiased, transparent and aligned with human values for real-world scenarios. · Create new techniques to ensure consistent alignment between user-centric explanations and intrinsic model behavior. · Reverse-engineer on neural networks to understand internal workings of AI models rather than treating them as "black boxes". · Develop data attribution methods to quantify the influence of specific data points (text and image) on a model's prediction and implement solution. · Implement and integrate AI explainbility techniques and tools. · Build rigorous benchmarks and datasets to measure the quality of explanations, model transparency, and effectiveness of treatments. · Communicate insights to stakeholders. Requirements: · Ph.D. in Computer Science, Deep Learning, Machine Learning, Mathematics or other related fields. · Focused on research in the AI field with good track records and high motivation in Explainable AI and Safety domain. · Strong proficiency in Large Language Models (LLMs), neural networks, and computer vision architectures. · Strong background in Python, Java, or C++, with deep knowledge of ML frameworks such as PyTorch, TensorFlow. · Successful experience in AI alignment to human values and expectations, model robustness improvement, controlled and continual learning, neural network interpretability and editing techniques is highly valued. · Pioneering novel methods and neural networks that revolutionized machine learning or the AI field, or revolutionized the industry, is a big bonus. · Strong publication record in top conferences (i.e. NeurIPS/ICLR/ICML/ AAAI/ACL/CVPR/ICCV/EMNLP/NAACL). · Candidates with ICPC, IOI/IMO, IOAI and other international competition in computer science, machine learning, and AI, etc. are highly preferred. · Good teamwork, enjoy working with multi‑culture teams, passionate in challenging the status quo. Why join us? Join a high‑caliber lab: Work in our Cloud Content Security Lab in Ruoholahti, Helsinki, alongside experienced international researchers and engineers in a focused environment that values scientific excellence, depth, and real impact to protect millions of Huawei Mobile users.

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Responsibilities

The researcher will develop techniques to make AI models more interpretable, transparent, and aligned with human values. They will also build benchmarks to measure model transparency and implement tools for AI explainability.