Applied Scientist (AI)

TL;DR

Applied Scientist (AI): Designing relevance metrics, building labeling pipelines, and fine-tuning language models to improve search quality with an accent on prompt engineering, modern language models techniques like Retrieval Augmented Generation, and scalable workflows for measurement and evaluation. Focus on accelerating career growth by working on state-of-the-art AI systems, developing deep expertise in prompt engineering and model tuning, and honing skills in building robust data pipelines and quality frameworks.

Location: Barcelona, Spain. Expected to work from the office at least four days per week if living within a 25-mile commute of a designated Microsoft office.

Company

hirify.global is a team powering business entity relevance on the search results page, leveraging large and small language models to deliver exceptional quality.

What you will do

• Design and implement new relevance metrics and optimize LLM/SLM labeling pipelines for local search quality.
• Engineer and fine-tune prompts for LLMs, applying modern techniques such as retrieval-augmented generation.
• Build scalable workflows and dashboards for measurement, evaluation cycles, and quality checks.
• Analyze failure modes and improve prompt rubrics to reduce defect rates and enhance labeling consistency.
• Collaborate with cross-functional teams to integrate metrics and labeling systems into production environments.

Requirements

• Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field with hands-on experience in statistics, predictive analytics, or research.
• OR Master’s Degree in a related field with hands-on experience in statistics, predictive analytics, or research.
• OR Doctorate in a related field.
• Microsoft Cloud Background Check is required.
• Expected to work from the Barcelona office at least four days per week if living within a 25-mile commute.

Culture & Benefits

• Accelerate career growth by working on state-of-the-art AI systems.
• Develop deep expertise in prompt engineering and model tuning.
• Hone skills in building robust data pipelines and quality frameworks.
• Contribute to a culture of inclusion built on values of respect, integrity, and accountability.
• Innovate to empower others and collaborate to realize shared goals.