Principal Applied AI Researcher – Agentic Search

This is a fully remote position, open to applicants in Europe.

📋 Description

• Create agent-centric retrieval systems that are optimized for machine interaction rather than human search experiences.

• Construct systems in which LLMs methodically plan, query, refine, and reason over the outcomes.

• Develop ranking and retrieval strategies for multi-step, agent-led workflows that operate under real-world limitations.

• Propel applied research and set the technical agenda for retrieval and ranking systems.

• Design and enhance multi-stage retrieval architectures, which encompass query understanding, rewriting, reranking, and iterative retrieval.

• Formulate techniques for grounding LLMs in real-time web data at scale.

• Define and execute evaluation frameworks and metrics for agent-driven systems.

• Lead experimentation on embeddings, hybrid search, and reranking, transitioning methodologies into production.

• Assess relevance, latency, and cost trade-offs on a large scale.

• Collaborate with engineering teams to implement systems in high-throughput, low-latency settings.

• Take ownership of ambiguous challenges from start to finish and influence product and research trajectories.

• Provide mentorship to engineers and contribute to elevating the technical standards of the team.

⛳️ Requirements

• Over 8 years of experience in applied AI, ML, or software engineering.

• Demonstrated history of deploying ML or AI systems to production at scale.

• Extensive experience with search, retrieval, ranking, recommendation systems, or assistants.

• Strong knowledge of modern deep learning techniques, particularly transformers and embeddings.

• Familiarity with LLM-integrated or knowledge-intensive systems.

• Experience in designing evaluation frameworks and metrics for ML systems.

• Proficient programming skills in Python and at least one of Go, C++, or comparable languages.

• Capability to thrive in a dynamic, product-focused environment, exhibiting high ownership and autonomy.

• Experience with large-scale search or recommendation systems.

• Background in agentic AI systems, including agents, tool utilization, or autonomous workflows.

• Familiarity with RAG, multi-step retrieval, or tool utilization.

• Publications, open-source contributions, or similar indicators of technical expertise and impact.

• Must have authorization to work in the country of application and provide proof of employment eligibility.

🏝️ Benefits

• Competitive compensation.

• Opportunities for career advancement and learning.

• Flexibility and a sense of ownership.

• A collaborative and innovative workplace culture.

• Chance to engage in impactful AI projects.

• An international environment with talented teams.

• A fast-paced work setting.

• Encouragement of bold thinking.

• Continuous growth.

• A chance to make a meaningful impact.

• An environment of trust and genuine ownership.

• Opportunity to influence the future of AI.

• Commitment to equal employment opportunities.

• Accommodations during the application process.