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Tech Stack
Tools & technologiesPythonPyTorch
About the role
Key responsibilities & impact- Define and drive the long-term strategy for search relevance, retrieval evaluation, ranking optimization, and AI system quality.
- Lead initiatives focused on improving:
- Search relevance and ranking quality.
- Semantic retrieval and vector search
- Retrieval-augmented generation (RAG)
- AI grounding and hallucination mitigation
- User discovery and engagement outcomes
- Establish scalable evaluation methodologies for search, retrieval, recommendation, and LLM-powered systems.
- Guide experimentation and optimization across lexical, semantic, hybrid, and AI-assisted retrieval architectures.
- Partner with Product and Engineering leadership to align search and AI investments with customer and business priorities.
- Influence technical direction for retrieval systems, evaluation infrastructure, and AI quality frameworks across platforms.
- Define and operationalize evaluation frameworks for search and generative AI systems.
- Build scalable processes for benchmark creation, annotation quality, evaluation governance, and performance reporting.
- Drive rigorous, evidence-based decision-making across AI and search initiatives.
- Champion responsible AI practices focused on quality, reliability, trust, and measurable user impact.
- Lead, mentor, and grow a high-performing team of Data Scientists and Analysts.
Requirements
What you’ll need- Master’s or PhD in Computer Science, Data Science, Machine Learning, Information Retrieval, Statistics, NLP, or a related quantitative field.
- 10+ years of experience in Data Science, Machine Learning, Information Retrieval, Search Relevance, Evaluation Systems, or Applied AI.
- Significant experience leading and scaling high-performing technical teams in complex, cross-functional organizations.
- Deep expertise in:
- Search relevance and ranking systems.
- Information retrieval and semantic search
- Retrieval-augmented generation (RAG)
- Evaluation methodologies for IR and generative AI systems
- Experimentation frameworks and A/B testing
- Strong experience with:
- Vector retrieval and hybrid search architectures.
- LLM evaluation and AI quality measurement
- Embeddings, reranking, and retrieval orchestration
- Evaluation datasets, benchmarking, and annotation workflows
- Advanced programming skills in Python.
- Experience with modern AI/ML frameworks and tooling (e.g., PyTorch, Hugging Face, LangChain, LangGraph, Haystack).
- Experience working with large-scale datasets, distributed data/ML platforms, and production AI systems.
- Strong understanding of statistical analysis, experimentation design, and evaluation science.
- Excellent communication and stakeholder management skills, including experience influencing senior leadership.
- Demonstrated ability to balance strategic leadership with pragmatic execution in rapidly evolving AI environments.
Benefits
Comp & perks- Comprehensive Pension Plan
- Home, office, or commuting allowance.
- Generous vacation entitlement and option for sabbatical leave
- Maternity, Paternity, Adoption, and Family Care leave
- Flexible working hours
- Personal Choice budget
- Internal communities and networks
- Various employee discounts
- Recruitment introduction reward
- Employee Assistance Program (global)
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
search relevanceranking optimizationsemantic retrievalvector searchretrieval-augmented generationevaluation methodologiesA/B testingstatistical analysisPythoninformation retrieval
Soft Skills
leadershipmentoringcommunicationstakeholder managementstrategic thinkingdecision-makingteam buildinginfluencingcollaborationexecution