21 days ago
United Kingdom (city not specified)Senior
Responsibilities
- Own competitive benchmarking initiatives across search, vector and hybrid retrieval, analytical, and observability workloads.
- Build and maintain automated benchmark harnesses, datasets, query sets, and load profiles representing real-world concurrency and ingestion patterns.
- Design fair comparisons with documented versions, configurations, tuning decisions, resource budgets, and functional differences.
- Measure latency distributions, throughput, resource consumption, cost efficiency, and retrieval quality at comparable relevance targets.
- Adapt and extend Elasticsearch Rally, ClickBench, and vector search benchmark frameworks.
- Investigate performance differences using profiling, system metrics, and controlled experiments, then validate engineering improvements.
- Evaluate self-managed and managed cloud deployments, including serverless offerings, scaling behavior, and service constraints.
- Publish reproducible benchmark artifacts and technical reports covering methodology, findings, limitations, and tradeoffs.
- Partner with engineering and product management to prioritize benchmark coverage and translate findings into product improvements.
Requirements
- Solid software engineering skills and experience building maintainable automation and analysis tools in Python or another relevant programming language.
- Hands-on experience evaluating and diagnosing performance in distributed systems, databases, or search infrastructure.
- Depth in at least one of search, vector retrieval, analytical databases, or observability systems, with the ability to learn unfamiliar systems.
- Experience designing representative datasets and workloads covering query patterns, concurrency, and ingestion behavior.
- Sound experimental judgment involving repeated measurements, variability analysis, warm-up and cache effects, and measurement-noise assessment.
- Experience building reproducible test environments and documenting configurations, procedures, and results.
- Clear technical writing and communication skills for explaining complex findings and limitations.
- Strong collaboration skills and the ability to turn performance evidence into actionable engineering recommendations.
- Bonus qualifications include experience with Elasticsearch, Lucene, Rally, ClickBench, vector search benchmark frameworks, retrieval-quality measurement, cloud performance and cost analysis, autoscaling, serverless systems, public technical writing, open-source contributions, or published benchmark studies.
Benefits
- Competitive pay based on the work performed, without salary figures stated.
- Health coverage for employees and families in many locations.
- Flexible locations and schedules with the ability to craft work calendars for many roles.
- Generous vacation allowance.
- Elastic matches up to $2000 or local-currency equivalent for financial donations and service.
- Up to 40 hours annually for volunteer projects.
- At least 16 weeks of parental leave.
- Distributed-company work environment with an emphasis on flexible work-life balance.
About Elastic
Elastic builds the Elasticsearch-based platform for enterprise search, observability (logging, metrics, APM), and security (SIEM/endpoint). It sells subscriptions and Elastic Cloud managed services with usage-based pricing, combining open source and proprietary features through Elasticsearch and Kibana. Founded in 2012 and headquartered in San Francisco, Elastic is publicly traded on the NYSE and is used by more than half of the Fortune 500.