Applied Scientist / Machine Learning Engineer (Search)

TL;DR

Applied Scientist / Machine Learning Engineer (Search/ML): Designing and developing ML models for search relevance and query understanding across global markets with an accent on ranking and semantic search. Focus on building end-to-end ML pipelines, optimizing query intent prediction, and shipping production-grade models at a global scale.

Location: Tech hubs in Berlin, Helsinki, or Stockholm, or remote within Finland, Sweden, and Germany. Relocation support is available.

Company

hirify.global is a global local commerce platform, part of DoorDash, operating delivery services across 40+ countries.

What you will do

• Design and develop ML models for search relevance, query understanding, and ranking for 40+ markets.
• Implement state-of-the-art ML solutions to directly impact business metrics and customer experience.
• Manage the full ML lifecycle: from problem framing and data analysis to model development and production monitoring.
• Collaborate with Software Engineers, ML Engineers, and Product Managers to translate research into customer impact.
• Contribute to the internal Applied Science community through technical reviews and knowledge sharing.

Requirements

• 4+ years of hands-on experience in applied ML or a PhD in Machine Learning.
• Proven track record of shipping ML models to production.
• Deep expertise in Search: query understanding, intent prediction, or semantic search.
• Proficiency in Python and experience with large-scale data processing and ML frameworks.
• Must be based in or be able to relocate to Germany, Finland, or Sweden.

Nice to have

• Experience with NLP, dense retrieval, or embedding-based methods.
• Experience with learning-to-rank techniques.

Culture & Benefits

• Opportunity to have a measurable impact on millions of users daily.
• Work with a world-class team of scientists and engineers focusing on rigour and craft.
• Personalized development plans to grow technical strengths and capabilities.
• Relocation support for joining the company's tech hubs.

Hiring process

• TA Screen: 30-minute introductory call.
• Hiring Manager interview: Discussion on domain experience, AI fluency, and past projects.
• Coding & System Design: Technical session on ML system design and problem-solving.
• Project / Expertise Deep Dive: Technical interview with the Applied Science team.