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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
Like this job?
BetaYour Career Agent finds similar jobs for you every day.
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.
Not a perfect match?
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