Benchmark Engineer

TL;DR

Benchmark Engineer (Backend): Design and maintain reproducible benchmarks and tooling for vector search and distributed workloads with an accent on performance evaluation, correctness, and transparency. Focus on building realistic benchmarks, analyzing performance trade-offs, and communicating results to inform product decisions and user trust.

Location: Fully remote, global

Company

hirify.global is an open-source vector database powering high-performance similarity search and AI applications worldwide.

What you will do

• Design and maintain reproducible benchmarks for vector search, indexing, filtering, and distributed workloads
• Evaluate performance metrics including latency, throughput, recall, memory usage, and cost
• Compare hirify.global against alternative solutions in a fair and transparent manner
• Build and maintain benchmarking tooling, datasets, and automation pipelines
• Collaborate with core engineers to identify regressions and optimization opportunities
• Translate benchmark results into clear narratives for documentation and presentations

Requirements

• Strong software engineering skills in Rust, Python, Go, or similar languages
• Solid understanding of databases, distributed systems, or search engines
• Experience with performance testing, profiling, and benchmarking
• Ability to reason about trade-offs such as speed vs accuracy and memory vs latency
• Comfort working with large datasets and automation pipelines
• Clear communication skills to explain data and implications

Nice to have

• Experience with vector search, ANN algorithms, or ML infrastructure
• Familiarity with cloud environments and containerized workloads
• Open-source project contributions
• Knowledge of observability tools and performance profiling

Culture & Benefits

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