Staff/Principal Applied ML Engineer (Search & Retrieval)

TL;DR

Staff/Principal Applied ML Engineer (Search & Retrieval): Design and own large-scale machine learning systems powering an agent-native search platform with an accent on retrieval, ranking, and indexing in high-throughput, low-latency environments. Focus on developing query understanding pipelines, optimizing relevance, latency, and cost, and operating production systems end-to-end.

Location: Amsterdam, Netherlands

Company

hirify.global leads a new era in cloud computing for the global AI economy, with headquarters in Amsterdam, Nasdaq listing, and R&D hubs across Europe, North America, and Israel.

What you will do

• Own end-to-end ML systems from problem definition to production and iteration
• Design and deploy models for retrieval, reranking, and search relevance
• Build and optimize large-scale embedding-based retrieval and indexing systems
• Develop query understanding, rewriting, and iterative retrieval pipelines
• Drive improvements in relevance, latency, and cost with evaluation frameworks
• Operate systems under low-latency, high-throughput constraints and collaborate with engineering teams
• Contribute to system architecture, technical direction, leadership, and mentorship

Requirements

• 8+ years in software engineering or applied machine learning
• Proven ownership of large-scale ML systems in production end-to-end
• Strong programming in Python and Go or C++
• Deep experience in search, recommendation systems, or ads ranking
• Hands-on with retrieval, ranking, or matching systems
• Experience operating high-throughput, low-latency production systems
• Strong understanding of modern ML including embeddings, transformers, ranking models
• Experience designing evaluation frameworks and metrics
• Ability to operate in ambiguity and drive problems end-to-end with trade-offs

Nice to have

• Experience with RAG, LLM-integrated systems, or agent-based architectures
• Experience with large-scale indexing, crawling, or data pipelines
• Familiarity with hybrid search (lexical and semantic)
• Experience with personalization or user modelling
• Contributions to open-source, publications, or technical talks

Culture & Benefits

• Competitive salary and comprehensive benefits package
• Opportunities for professional growth
• Flexible working arrangements
• Dynamic and collaborative work environment valuing initiative and innovation

Hiring process

• Coding interviews as part of the process