2025 - Senior Ads Recommendation Scientist - Huawei Petal Ads - Contractor

Location: Dublin, Ireland

About Huawei

Huawei is a leading global information and communications technology (ICT) infrastructure and smart devices provider. With integrated solutions across four key domains – telecom networks, IT, smart devices, and cloud services – we are committed to bringing digital to every person, home, and organisation for a fully connected, intelligent world.

About Huawei Petal Ads

Petal Ads is a smart marketing platform for Huawei devices. It provides marketing and traffic monetisation services for advertisers and publishers worldwide to help them achieve business growth and improve brand value. It does this by leveraging Huawei's "1+8+N" all-scenario ecosystem, Huawei apps' marketing capabilities, massive premium third-party traffic, and powerful ad technologies. Petal Ads has a global user base of more than 730 million monthly active users covering 220+ Global markets, while more than 60,000 apps worldwide have integrated Ads Kit. In addition, 20+ Huawei apps and 10+ mainstream ad formats are at users' disposal.

About the Job:

As a Senior Data Scientist in Huawei Ads, you will join a world-class team of experts to apply advanced machine learning, statistics, and mathematical modelling to one of the largest-scale advertising and recommendation platforms. You will leverage your strong industrial and academic background to design and deploy cutting-edge algorithms that directly impact Huawei’s global advertising ecosystem.

We are seeking a highly skilled and experienced domain expert who is passionate about recommender systems and computational advertising. You will tackle challenging problems at the intersection of academic research and applied industrial practice—ranging from personalisation, ranking, and reinforcement learning to large-scale model deployment. Your work will help shape the future of user and advertiser experience within Huawei Ads and accelerate global business growth.

Our team collaborates closely with Huawei’s recommendation, search, and cloud service groups, as well as AALA and HQ experts. This role provides you with opportunities to validate ideas quickly, influence cross-functional strategies, and contribute to both production innovation and cutting-edge research.

Responsibility:

• Conduct research,
  development, and deployment of innovative recommendation and advertising
  algorithms, including but not limited to:




• Personalised
  ranking models
  (pCTR/pCVR prediction, multi-task learning, representation learning).


• Ads and
  content recommendation (user-ad matching, contextual targeting, multi-modal signals).


• Sequential
  and session-based recommendation (deep learning, transformers, graph-based models).


• Fairness,
  diversity, and long-term value optimisation in recommendation.




• Drive improvements in ad data
  reliability, efficiency, and quality by leveraging large-scale
  recommendation datasets (structured, unstructured, and multi-modal).


• Design and evaluate A/B tests
  and statistical experiments to measure the effectiveness of algorithms and
  new recommendation features.


• Monitor, analyse, and tune
  model performance across core recommendation and advertising KPIs (RPM,
  eCPM, engagement, retention, relevance).


• Collaborate with product
  managers, engineers, and domain experts to translate business needs into
  scalable, recommendation-driven solutions.


• Stay ahead of emerging trends
  in recommender systems (e.g., self-supervised learning, foundation models
  for recsys, retrieval-augmented models, federated learning for
  privacy-preserving recommendations).

Requirements:

• Master’s or PhD in a
  quantitative discipline (Computer Science, Information Systems,
  Mathematics, Statistics, Physics, or related).


• 4+ years of proven experience
  in delivering large-scale machine learning products, with a focus on
  recommender systems, personalisation, or ranking.


• Strong expertise in machine
  learning for recommendation: collaborative filtering, matrix factorisation, deep
  learning (DNNs, transformers, graph neural networks), reinforcement
  learning, or bandit algorithms.


• Hands-on experience with
  recommender system frameworks and libraries (e.g., TensorFlow
  Recommenders, PyTorch).


• Solid programming skills in Python and experience in production
  ML pipelines.


• Strong analytic and
  experimental design skills for A/B testing and offline evaluation of
  recommendation models.


• Proficiency in SQL or Hive
  SQL with an understanding of distributed data processing and query
  optimisation.


• Excellent written and oral
  communication skills for presenting complex recommendation solutions to
  both technical and non-technical stakeholders.


• (Preferred) 2+ years of
  direct experience in computational advertising, recommender systems in
  large-scale platforms, or working with advertising/recommendation
  datasets.

Check out Life at Huawei Ireland Research Centre: https://www.youtube.com/watch?v=3gR64sYSnOA&feature=youtu.be

ONLY CANDIDATES WHO MAY LIVE AND WORK IN IRELAND WITHOUT RESTRICTION CAN BE CONSIDERED FOR THIS POSITION.

DUE TO THE HIGH VOLUME OF REPLIES, ONLY CANDIDATES WHO ARE SHORTLISTED FOR INTERVIEW WILL BE CONTACTED.

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