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Validation Engineer - Context, Semantics & Memory(m/w/x)
Designing and operating knowledge graphs and graph databases for automotive AI. Expert programming skills in Python or Java required. 6 weeks annual leave, overtime compensation.
Requirements
- University degree in Computer Science, Information Science, AI/ML, or related field
- Expert programming skills in C++, Java, Kotlin, or Python
- Proficiency in AI-assisted development (Claude Code, GitHub Copilot, OpenCode)
- Experience building/querying knowledge graphs (RDF/SPARQL, property graphs) and integrating with LLM retrieval (GraphRAG, hybrid search)
- Experience with systems design for knowledge-intensive or retrieval-heavy architectures
- Familiarity with agent memory architectures, ontology design, semantic modelling, graph-based analytics, entity resolution, or knowledge-graph embeddings
- Enjoyment of international team work and passion for software quality
Tasks
- Design and operate knowledge graphs and graph databases
- Capture domain knowledge, toolchain topology, operational incidents, and root-cause analyses
- Enable graph-based retrieval across the organization
- Build context-engineering pipelines for dynamic information assembly and ranking
- Implement feedback loops for agent interactions and skill development
- Log outcomes, diagnose failures, and write findings back into the knowledge graph
- Develop and maintain ontologies and semantic models for the automotive AI domain
- Ensure consistent vocabulary across teams and tools
- Architect agent memory systems with consolidation and retention mechanisms
- Optimize retrieval quality using relevance, coverage, freshness, and redundancy metrics
- Run experiments comparing retrieval strategies
- Contribute to cost-efficient model selection and context-compression strategies
- Keep latency low and budgets sustainable at scale
Work Experience
- 1 - 3 years
Education
- Bachelor's degree
Languages
- English – Business Fluent
Tools & Technologies
- C++
- Java
- Kotlin
- Python
- Claude Code
- GitHub Copilot
- OpenCode
- RDF
- SPARQL
- GraphRAG
Benefits
Flexible Working
- Flexible working hours
More Vacation Days
- 6 weeks annual leave
Competitive Pay
- Overtime compensation
Bonuses & Incentives
- Christmas bonus
- Profit sharing
Diverse Work
- Challenging projects
Learning & Development
- Personal and professional development opportunities
Job Security
- High job security
Corporate Discounts
- Discounted BMW & MINI conditions
Other Benefits
- Many other benefits
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Validation Engineer - Context, Semantics & Memory(m/w/x)
Designing and operating knowledge graphs and graph databases for automotive AI. Expert programming skills in Python or Java required. 6 weeks annual leave, overtime compensation.
Requirements
- University degree in Computer Science, Information Science, AI/ML, or related field
- Expert programming skills in C++, Java, Kotlin, or Python
- Proficiency in AI-assisted development (Claude Code, GitHub Copilot, OpenCode)
- Experience building/querying knowledge graphs (RDF/SPARQL, property graphs) and integrating with LLM retrieval (GraphRAG, hybrid search)
- Experience with systems design for knowledge-intensive or retrieval-heavy architectures
- Familiarity with agent memory architectures, ontology design, semantic modelling, graph-based analytics, entity resolution, or knowledge-graph embeddings
- Enjoyment of international team work and passion for software quality
Tasks
- Design and operate knowledge graphs and graph databases
- Capture domain knowledge, toolchain topology, operational incidents, and root-cause analyses
- Enable graph-based retrieval across the organization
- Build context-engineering pipelines for dynamic information assembly and ranking
- Implement feedback loops for agent interactions and skill development
- Log outcomes, diagnose failures, and write findings back into the knowledge graph
- Develop and maintain ontologies and semantic models for the automotive AI domain
- Ensure consistent vocabulary across teams and tools
- Architect agent memory systems with consolidation and retention mechanisms
- Optimize retrieval quality using relevance, coverage, freshness, and redundancy metrics
- Run experiments comparing retrieval strategies
- Contribute to cost-efficient model selection and context-compression strategies
- Keep latency low and budgets sustainable at scale
Work Experience
- 1 - 3 years
Education
- Bachelor's degree
Languages
- English – Business Fluent
Tools & Technologies
- C++
- Java
- Kotlin
- Python
- Claude Code
- GitHub Copilot
- OpenCode
- RDF
- SPARQL
- GraphRAG
Benefits
Flexible Working
- Flexible working hours
More Vacation Days
- 6 weeks annual leave
Competitive Pay
- Overtime compensation
Bonuses & Incentives
- Christmas bonus
- Profit sharing
Diverse Work
- Challenging projects
Learning & Development
- Personal and professional development opportunities
Job Security
- High job security
Corporate Discounts
- Discounted BMW & MINI conditions
Other Benefits
- Many other benefits
About the Company
BMW Group
Industry
Automotive
Description
Das Unternehmen bietet spannende Praktika im Bereich Markenerlebnis und Eventmanagement und legt großen Wert auf Gleichbehandlung und Chancengleichheit.
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