Senior Applied Data Scientist (AI)

TL;DR

Senior Applied Data Scientist (Retrieval/Semantic Systems): Designing and implementing end-to-end retrieval and semantic systems to power AI-native capabilities across the platform with an accent on vector store operation, indexing pipelines, and hybrid retrieval. Focus on building robust retrieval evaluation systems, optimizing relevance and latency, and scaling advanced AI research into reliable production features.

Location: Hybrid (Budapest, Hungary)

Company

hirify.global creates intuitive products and AI-native capabilities that simplify learning and personal development within the educational technology sector.

What you will do

• Design, build, and ship production retrieval systems that power AI capabilities across multiple products.
• Manage vector store selection and operation, ensuring scalability, latency, and multi-tenant design.
• Build and operate indexing and refresh pipelines, including chunking and embedding generation.
• Implement semantic and hybrid retrieval using embeddings, similarity search, and reranking.
• Establish retrieval evaluation systems using gold sets, relevance metrics, and regression gates.
• Collaborate with AI Platform and infrastructure engineers on deployment and observability.

Requirements

• 6+ years of experience building and shipping production machine learning or applied AI systems.
• Proven ownership of a production retrieval system, including vector store selection.
• Strong Python skills and experience building services and APIs (e.g., FastAPI).
• Deep grounding in embeddings, approximate nearest neighbor (ANN) search, and ranking systems.
• Experience designing indexing strategies with data quality controls and safe backfills.
• Ability to define and execute retrieval evaluation and analyze failures by slice.

Nice to have

• Experience with hybrid retrieval, learning to rank, or domain-specific reranking.
• Knowledge of integrating graph-structured context or knowledge graphs into retrieval.
• Experience with evaluation and observability for LLM and retrieval systems.
• Proficiency with AWS-native retrieval and indexing architectures.
• Experience in edtech, content, curriculum, or skills modeling.

Culture & Benefits

• Competitive compensation and participation in the company ownership program.
• Flexible work culture with remote, hybrid, and in-office options.
• Generous time off, including the annual “Dim the Lights” recharge period in December.
• Comprehensive wellness programs and mental health support.
• Learning and development resources, including tuition reimbursement.
• Inclusivity-rooted culture with employee recognition via Motivosity.