Remote Senior E-commerce Search & Recommendation Engineer

Randstad Singapore; Singapore; On-site; SGD 180,000 - 260,000; Full time

Job summary

Randstad Singapore seeks a Staff or Principal Engineer to lead the development of next‑gen search and recommendation systems for a global e‑commerce platform. You will architect low-latency ranking pipelines and harness semantic search to boost relevance.

Collaborate with data scientists and engineers to build real-time models using embeddings, LTR, and NLP, and drive experimentation pipelines to scale production.

Qualifications

• Bachelor's degree in Computer Science, or equivalent.
• Minimum 7 years of experience in large-scale e-commerce search or information retrieval.
• Strong mastery of semantic search, vector embeddings, Learning-to-Rank, and NLP frameworks.
• Proficiency in Python/Java/C++ and modern ML libraries (PyTorch, TensorFlow).

Responsibilities

• Build and optimize personalized recommendation algorithms within the search journey (e.g., semantic search, query-based product suggestions)
• Develop deep learning models that blend real-time query intent with historical user data for hyper-personalized ranking
• Architect low-latency, multi-stage retrieval and ranking engines to boost conversion, CTR, and relevance metrics
• Introduce cutting-edge AI to search discovery
• Design rigorous experimentation frameworks to validate and scale algorithms in production

Skills

Semantic search

Vector embeddings

Learning-to-Rank

NLP frameworks

Python

Java

C++

PyTorch

TensorFlow

Spark

Elasticsearch/OpenSearch

Distributed processing

Search engines

Education

Bachelor's degree in Computer Science

Tools

PyTorch

TensorFlow

Spark

Elasticsearch/OpenSearch

Vector DBs

Job description

Randstad Singapore seeks a Staff or Principal Engineer to lead the development of next‑gen search and recommendation systems for a global e‑commerce platform. You will architect low-latency ranking pipelines and harness semantic search to boost relevance.

Collaborate with data scientists and engineers to build real-time models using embeddings, LTR, and NLP, and drive experimentation pipelines to scale production.