Job Description, Responsibilities & Requirements
About the Position
We are looking for a highly skilled Senior AI Engineer to join our growing engineering team and lead the development of next-generation search, ranking, and AI-driven matching systems. This role combines machine learning, information retrieval, LLMs, and document understanding to build intelligent products that deliver measurable business impact.
You will play a key role in designing, implementing, and optimizing ranking systems from the ground up, working across retrieval, feature engineering, weak supervision, model evaluation, and production deployment. The ideal candidate is comfortable operating in fast-moving environments, taking ownership of complex problems, and delivering practical solutions that balance performance, scalability, and business needs.
Responsibilities
- Design, build, and optimize recommendation, ranking, and semantic matching systems.
- Develop candidate-job matching algorithms using structured and semantic signals.
- Build and improve retrieval pipelines combining lexical search, embeddings, and vector search.
- Design ranking and re-ranking systems to maximize relevance and matching quality.
- Develop Learning-to-Rank models using LambdaMART, XGBoost, and LightGBM.
- Create feature engineering pipelines for ranking, matching, and recommendation systems.
- Improve retrieval precision, recall, and overall search relevance.
- Build evaluation frameworks using ranking metrics such as NDCG, MRR, Precision@K, and Recall@K.
- Leverage LLMs for label generation, weak supervision, pairwise preference modeling, and dataset creation.
- Design evaluation loops for LLM-generated supervision and ranking improvements.
- Improve OCR, CV parsing, and document understanding pipelines.
- Extract, normalize, and structure information from resumes and other unstructured documents.
- Collaborate closely with product and engineering teams to build transparent and explainable ranking systems.
Requirements
Ranking, Recommendation/ Matching Systems
- Strong expertise in Python
- Experience building and operating ML systems in production
- Deep understanding of Learning-to-Rank methodologies, particularly LambdaMART.
- Hands-on experience with XGBoost and LightGBM.
- Experience designing ranking and re-ranking pipelines.
- Strong experience building recommendation, ranking, matching, or search systems in production.
- Strong understanding of ranking metrics including: NDCG, MRR, Precision@K, Recall@K
- Experience improving ranking quality and relevance.
- Expertise in feature engineering for ranking and matching systems.
- Strong understanding of recall vs. precision trade-offs.
- Experience building systems without large-scale historical behavioral data.
- Experience improving explainability and trust in ranking outputs.
NLP/Semantic Understanding
- Strong NLP expertise and experience working with text-heavy datasets.
- Experience with semantic matching between resumes and job descriptions.
- Strong understanding of embeddings, vector representations, and semantic similarity.
- Experience building candidate similarity and text comparison systems.
- Experience extracting and normalizing skills from unstructured text.
- Strong understanding of transformer architectures and modern NLP techniques.
- Practical experience fine-tuning transformer models.
Search/ Retrieval
- Experience building hybrid search systems combining BM25 and semantic retrieval.
- Experience with vector search and embedding-based retrieval architectures.
- Familiarity with Vespa, Elasticsearch, OpenSearch, or similar search platforms.
- Experience designing embedding generation pipelines.
- Strong understanding of retrieval optimization and relevance tuning.
LLMs/ Applied AI
- Experience using LLMs for: Label generation, Weak supervision, Pairwise preference modeling, Data enrichment
- Experience with LangGraph, LangChain, LangSmith, LangFuse, or similar frameworks.
- Familiarity with the Hugging Face ecosystem.
- Ability to design evaluation frameworks for LLM-generated supervision.
Document Understanding. Information Extraction
- Experience building or improving OCR pipelines.
- Experience with CV parsing and structured data extraction.
- Familiarity with layout-aware document understanding models.
- Experience extracting structured information from complex documents.
- Understanding how extraction quality impacts downstream ranking and matching performance.
Engineering / Production Systems
- Strong Python engineering skills.
- Practical experience with PyTorch.
- Experience building and operating ML systems in production.
- Understanding of model serving architectures.
- Experience designing scalable, reliable, and cost-efficient AI systems.
- Experience building experimentation and evaluation frameworks from scratch.
Nice to Have
- Experience in HRTech, recruitment platforms, talent intelligence, or hiring products
- Experience building candidate-job matching systems
- Experience working with recommendation engines at scale
- Experience improving semantic relevance in search or matching products.
We Offer
- Opportunity to shape core AI and search capabilities in a rapidly growing product.
- High-impact role with significant ownership and autonomy.
- Flexible working arrangements, including remote or hybrid options.
- Collaborative, multicultural, English-speaking environment.
- Modern engineering culture focuses on innovation, experimentation, and continuous learning.
- Learning and development support, including conferences, courses, and certifications.
- Career growth opportunities within a fast-scaling organization.
- Access to mentorship, coaching, and leadership development.
- Flat organizational structure with fast decision-making processes.
- Relocation and visa support where applicable.
About the Company
Join our dynamic team in Luxembourg and contribute to building intelligent products that deliver measurable business impact.
Work type: Full-time
Department: Research & Development
Division: Europe
Location: Luxembourg