We are seeking a pragmatic and analytical Search Relevance Engineer to join our search team. The successful candidate will drive improvements to search ranking, relevance and user satisfaction through rigorous experimentation, data analysis and machine learning. This role suits someone comfortable working across engineering and product with a strong focus on metrics and scalable solutions.
Search Relevance Engineer Job Profile
The Search Relevance Engineer will own the quality of search results across products and platforms. You will collaborate with engineers, data scientists and product managers to design experiments, craft features and evaluate ranking signals.
Reporting to the Search Lead, you will balance hands on model development with production engineering, monitoring and continuous tuning to meet business and user experience goals.
Search Relevance Engineer Job Description
As a Search Relevance Engineer you will analyse user queries and behaviour to identify relevance gaps and improvement opportunities. You will develop and deploy ranking models and features informed by both classical information retrieval and modern machine learning techniques. Your work will include feature engineering, offline evaluation, and building pipelines that can scale to millions of queries.
You will design and run A B tests and online experiments to measure the impact of relevance changes on engagement, conversion and satisfaction metrics. Regularly reviewing relevance metrics, error analyses and query segments will be central to prioritising work. You will also document findings and present recommendations to stakeholders, translating technical outcomes into business impact.
The role requires close collaboration with infra and backend engineers to ensure models and features are robust in production. You will implement monitoring and alerting for relevance regressions and lead post mortems on experiments that fail to meet expectations. Where appropriate, you will automate tuning workflows and integrate feedback loops from user interactions into model updates.
Search Relevance Engineer Duties and Responsibilities
- Analyse search logs and user behaviour to identify relevance issues and improvement opportunities.
- Design, implement and evaluate ranking features and models using IR and ML techniques.
- Run A B tests and online experiments to measure impact on engagement and conversion.
- Build robust pipelines for feature extraction, training and model serving in production.
- Develop offline evaluation frameworks and relevance metrics to guide development.
- Collaborate with product, engineering and data teams to prioritise and deliver solutions.
- Monitor production relevance, set alerts and lead investigations into regressions.
- Perform query intent analysis and segment-specific tuning for improved user experience.
- Document work, produce reproducible analyses and present results to stakeholders.
- Maintain data privacy and compliance when using user data for model training and evaluation.
Search Relevance Engineer Requirements and Qualifications
- Degree in Computer Science, Mathematics, Statistics or related field, or equivalent experience.
- Proven experience in search, information retrieval or recommendation systems.
- Strong programming skills in Python, and familiarity with production systems and APIs.
- Experience with machine learning libraries and model deployment frameworks.
- Practical knowledge of A B testing, experiment design and statistical analysis.
- Familiarity with ranking algorithms, relevance metrics and query understanding techniques.
- Experience with big data tools and workflow orchestration is desirable.
- Excellent communication skills and ability to translate technical findings into business outcomes.
- Attention to detail, strong analytical mindset and a user centric approach.
- Ability to work independently and as part of a cross functional team in an agile environment.
