Senior Data Scientist - (Global Search, Consumer) (AI)

Location: Berlin, Germany; hybrid work with attendance at the Berlin campus 2 days per week. Relocation support to Berlin is available.

Company

hirify.global operates a local delivery and quick-commerce platform across around 65 countries, with its headquarters in Berlin.

What you will do

• Design, build, and productionize deep neural ranking models, including DCN-V2, MMoE, and Two-Tower architectures.
• Own the ranking model lifecycle from offline experimentation and evaluation through deployment, monitoring, and iterative improvement.
• Develop agentic experimentation workflows using LLM coding agents to automate feature engineering and Learning to Rank architecture research.
• Improve ranking quality through ranking signals, feature stores, embedding-based retrieval, and production-grade model architecture innovation.
• Monitor model drift, serving latency, feature pipeline integrity, and data quality across high-throughput search systems.
• Collaborate with backend engineers, data engineers, and product managers while mentoring junior and mid-level data scientists.

Requirements

• 4+ years of industry experience as a Data Scientist or Machine Learning Engineer in high-traffic production environments.
• Master’s degree, or Bachelor’s degree with 6+ years of work experience, in Computer Science, Mathematics, Physics, or a related quantitative field.
• Production experience with deep learning ranking architectures, Learning to Rank methods, multi-task learning, cross-feature interactions, and embedding optimization.
• Proficiency with LLM coding agents and agentic CLI tools for autonomous experiment generation, architecture prototyping, and iterative development.
• Expertise in Python, PyTorch, TensorFlow, scikit-learn, SQL, dbt, GCP or AWS, PySpark, and Scala.
• Experience with feature stores, vector databases, model versioning, A/B testing, CI/CD for ML pipelines, Metaflow, experiment tracking, model registries, and production monitoring.

Nice to have

• Familiarity with the auto-research paradigm and reviewing large volumes of autonomously generated experiments.
• Experience translating academic advances in ranking and machine learning into production systems.

Culture & Benefits

• Hybrid work with face-to-face collaboration at the Berlin campus.
• 27 days of annual leave, increasing with service.
• €1,000 educational budget, language courses, parental support, and Udemy Business access.
• Health checkups, meditation and gym benefits.
• Employee Share Purchase Plan, sabbatical bank, public transportation discount, life and accident insurance, and corporate pension plan.
• Digital meal and food vouchers, plus relocation support for moving to Berlin.

Hiring process

• Interview preparation materials and an interview process managed in collaboration with recruiters.