What is The Role:
The Search Conversational Experiences team builds Elastic’s new conversational and agentic platform that lets customers chat with their own data in Elasticsearch. We build the core quality layer for RAG, agents and tools, retrieval and citations, streaming, memory, and the evaluation signals that turn open‑ended questions into grounded, reliable answers. As a Principal Data Scientist, you will help set the technical direction for how we evaluate, improve, and scale chat quality across Elastic’s agentic platform. You will define the evaluation strategy that guides product decisions, including which models we standardize on, how we route requests across agents, which tools we enable and when, and how we tailor agents to different Elastic use cases in search and beyond. You will work closely with backend engineering, product, UX, and other data scientists to turn ambiguous, cutting‑edge problems into measurable product improvements.
What You Will Be Doing:
- Define the evaluation strategy for conversational and agentic search, including offline and online evaluation, golden datasets, rubrics, LLM‑as‑judge calibration, groundedness and citation checks, and A/B testing.
- Lead the design of quality metrics and decision frameworks for RAG, agents, tools, model selection, agent routing, prompt behaviour, and cost/latency trade‑offs.
- Build, compare, and guide improvements across retrieval and re‑ranking approaches, including sparse and dense retrieval, vector search, query understanding, semantic rewrites, and context enrichment.
- Turn experimental results into product and business decisions: which models to use, how to route requests efficiently, which tools should be exposed, and how agents should be customised for different Elastic use cases.
- Partner with engineering to productionise evaluation pipelines, telemetry, dashboards, CI guardrails, and regression detection for chat quality, helpfulness, dedication, latency, and cost.
- Influence the roadmap by identifying the highest‑leverage quality gaps, proposing practical solutions, and communicating trade‑offs clearly to product, engineering, and leadership.
- Mentor other data scientists and engineers in experiment design, evaluation methodology, statistical rigor, and practical approaches to improving LLM‑powered systems.
- Share outcomes through clear docs, notebooks, PRs, dashboards, technical proposals, and cross‑functional reviews.
What You Bring:
- 8+ years of applied DS/ML experience, with deep expertise in IR, NLP, ranking, semantic search, RAG, or LLM‑powered product experiences.
- Strong track record defining and leading evaluation for production AI/ML systems, including offline metrics, online experimentation, LLM‑as‑judge approaches, groundedness, citation quality, and model comparison.
- Experience influencing product and technical strategy through data, especially in ambiguous or emerging domains where the “right” metric or approach is not obvious at the start.
- Hands‑on ability with Python, PyTorch/Transformers, Pandas, notebooks, reproducible experiments, versioned datasets, and clean, reviewable code.
- Strong understanding of retrieval systems, including dense and sparse retrieval, re‑ranking, vector search, query understanding, and evaluation metrics such as nDCG, MRR, Recall@k, precision, and latency/cost trade‑offs.
- Experience collaborating closely with engineering teams to move from prototype to production, including telemetry design, dashboards, CI guardrails, and quality regression tracking.
- Practical Elasticsearch experience, or experience with similar search and distributed data systems. ES|QL familiarity is a plus.
- Excellent written and verbal communication, with the ability to explain complex scientific and technical trade‑offs to engineering, product, design, and leadership audiences.
- A collaborative, low‑ego style and a strong ability to mentor, raise standards, and develop transparency for others in a distributed team.
Benefits:
- Competitive pay based on the work you do here and not your previous salary.
- Health coverage for you and your family in many locations.
- Flexible locations and schedules for many roles.
- Generous number of vacation days each year.
- We match up to €2000 (or local currency equivalent) for financial donations and service.
- Up to 40 hours each year to use toward volunteer projects you love.
- Minimum of 16 weeks of parental leave.
Security & Privacy Responsibilities:
Take ownership of protecting the confidentiality, integrity, and availability of organizational data and systems by following applicable privacy and security policies, standards, and procedures. Ensure that all individual contributions follow Elastic’s Secure Software Development Framework (SSDF). Proactively participate in mandatory role‑based training to ensure personal technical execution consistently aligns with the highest standards of data protection, data privacy, and system resilience.
Equal Opportunity Employer
Elastic is an equal‑opportunity employer and is committed to creating an inclusive culture that celebrates different perspectives, experiences, and backgrounds. Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, pregnancy, sexual orientation, gender identity or expression, national origin, age, marital status, protected veteran status, disability status, or any other basis protected by federal, state or local law, ordinance or regulation.
Accommodation & Legal Rights
We welcome individuals with disabilities and strive to create an accessible and inclusive experience for all. To request an accommodation during the application or recruiting process, please email candidate_accessibility@elastic.co. Applicants have rights under Federal Employment Laws and can view the following posters linked below: Family and Medical Leave Act (FMLA) Poster, Equal Employment Opportunity (EEO) Poster, and Employee Polygraph Protection Act (EPPA) Poster. Compensation for this role is base salary only; variable pay is not included.
Compensation
Typical starting salary range: €73,300—€115,900 EUR.
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