Benchmark Engineer

Qdrant is an open-source vector database built for high-performance similarity search and AI applications. We power production-grade semantic search recommendation systems and RAG pipelines for teams worldwide. As AI adoption accelerates performance correctness and transparency matter more than ever and thats where you come in.

The Role

Were looking for a Benchmark Engineer to own and evolve how we measure validate and communicate Qdrants performance. Youll design realistic benchmarks build tooling around them and transform raw numbers into actionable insights that inform product decisions documentation and user trust.

This role sits at the intersection of engineering performance and developer experience.

Tasks

What Youll Do

• Design and maintain reproducible benchmarks for vector search indexing filtering and distributed workloads
• Evaluate performance across different dimensions: latency throughput recall memory usage and cost
• Compare Qdrant against alternative solutions in a fair transparent and technically sound way
• Build and maintain benchmarking tooling datasets and automation (CI dashboards reports)
• Collaborate closely with core engineers to identify regressions bottlenecks and optimization opportunities
• Help translate benchmark results into clear narratives for docs blog posts and talks
• Ensure benchmarks reflect real-world user workloads not just synthetic best cases

Requirements

What Were Looking For

• Strong software engineering background (Rust Python Go or similar)
• Solid understanding of databases distributed systems or search engines
• Experience with performance testing profiling and benchmarking
• Ability to reason about trade-offs (speed vs accuracy memory vs latency etc.)
• Comfort working with large datasets and automation pipelines
• Clear communication skills you can explain numbers and their implications

Nice to Have

• Experience with vector search ANN algorithms or ML infrastructure
• Familiarity with cloud environments and containerized workloads
• Experience contributing to open-source projects
• Knowledge of observability tools and performance profiling

Benefits

Why Join Qdrant

• Work on core infrastructure for modern AI systems
• Open-source engineering-driven culture
• Fully remote team with flexible working hours
• High ownership real impact and technical depth
• Opportunity to shape how the industry evaluates vector databases

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