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Algorithm Expert (Search and Recommendation)

Job description

Responsibilities

  • Contribute to the research and development of advanced search technologies for applications and diversified digital services within a large‑scale app ecosystem.
  • Lead end‑to‑end development and integration of recall and ranking algorithms, ensuring high‑quality search relevance and performance.
  • Design and execute A/B tests and experimental frameworks to evaluate and compare search and recommendation models, ensuring continuous optimization.
  • Explore and apply cutting‑edge AI technologies-including information retrieval, ranking models, LLMs, and next‑generation search & recommendation methodologies-to drive product innovation.

Requirements

  • PhD strongly preferred, with an academic background in Computer Science, Engineering, or related fields.
  • Minimum 3 years of leadership or team management experience in search engine technology or a closely related domain.
  • Strong expertise in data structures, algorithms, machine learning, deep learning, NLP, LLMs, and big‑data analytics.
  • Hands‑on programming proficiency in Python, Java, or Scala, along with solid experience using modern deep learning frameworks (e.g., TensorFlow, PyTorch).
  • Proven research or project experience in areas such as search engines, online advertising, generative AI, or other large‑scale AI application domains.
  • Ability to diagnose complex business and technical issues using large‑scale data, identify root causes swiftly, and deliver effective, practical solutions.
  • Excellent communication skills, strong ownership mindset, and the ability to collaborate effectively within cross‑functional teams.

Interested applicants please send your resume in MS Words format to pooja.yadav@ambition.com.sg and attention to Pooja Yadav (R1551322)

Short listed candidates will be notified

www.ambition.com.sg

EA Registration Number: R1551322

Data provided is for recruitment purposes only

Business Registration Number: 200611680D.

License Number: 10C5117