Applied AI Engineer - Semantic Search & Job Matching

JobLeads GmbH; United States; Remote; USD 140,000 - 210,000; Full time

Job summary

JobLeads GmbH is seeking an Applied AI Engineer to build the intelligence behind how candidates and jobs find each other—semantic search, resume-based matching, and LLM-driven query understanding. You will design retrieval systems at scale and own the evaluation framework, benchmarking, and A/B testing.

The role emphasizes hands-on experimentation, prototype development, and collaboration with engineers to productionize winners quickly, leveraging cutting-edge models and research.

Qualifications

• Degree in Computer Science, AI, or a related field from a top-tier program.
• Hands-on experience building applied ML or LLM systems that real users touched.
• Genuine data-science depth: design experiments, baselines, and reason about metrics.

Responsibilities

• Design and improve retrieval systems over a large real-world corpus at scale (embeddings, hybrid search, ranking).
• Shape the design of vector search backbone and embedding models.
• Build LLM pipelines for understanding queries, resumes, and jobs including extraction, enrichment, and matching.
• Own evaluation as a scientific discipline, curate benchmark datasets capturing failure modes and healthy cases.
• Read results like a scientist and quantify quality, latency, and cost per query.
• Build interactive prototypes for product teams and ship winners to production.

Skills

Applied ML/LLM systems

Python

Experiment design

End-to-end pipeline

Data science depth

Communication

CS/AI degree

Education

CS/AI degree

Tools

Python

Job description

JobLeads GmbH is seeking an Applied AI Engineer to build the intelligence behind how candidates and jobs find each other—semantic search, resume-based matching, and LLM-driven query understanding. You will design retrieval systems at scale and own the evaluation framework, benchmarking, and A/B testing.

The role emphasizes hands-on experimentation, prototype development, and collaboration with engineers to productionize winners quickly, leveraging cutting-edge models and research.