Remote's Total Rewards philosophy is to ensure fair, unbiased compensation and fair equity pay along with competitive benefits in all locations in which we operate. We do not agree to or encourage cheap-labor practices and therefore we ensure to pay above in-location rates. At Remote, we foster internal mobility as a key element of our culture of employee growth and development, supported by a compensation philosophy that guarantees pay equity and fairness.
Principal Data Scientist - Agent Builder
Location
Spain
Posted
5 days ago
Salary
0
Seniority
Lead
Job Description
Principal Data Scientist - Agent Builder
Referral Board
Role Description 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. - Work closely with backend engineering, product, UX, and other data scientists. - Lead work on frontier problems such as folding RAG and vector search into an agent’s knowledge base. - Prototype, evaluate, influence roadmap direction, and help teams ship improvements that customers can feel. 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 behavior, 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. - Partner with engineering to productionize 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. Qualifications - 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. - Experience influencing product and technical strategy through data. - 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. - Experience collaborating closely with engineering teams to move from prototype to production. - Practical Elasticsearch experience, or experience with similar search and distributed data systems. - Excellent written and verbal communication skills. - A collaborative, low-ego style and a strong ability to mentor. 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. - Ability to craft your calendar with 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.
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