21 days ago
Base Salary
$133k - $211k/yr
Responsibilities
- Own prioritized 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 usage.
- Design fair comparisons with documented versions, configurations, tuning decisions, resource budgets, and functional differences.
- Evaluate latency distributions, throughput, resource consumption, cost efficiency, and retrieval quality.
- Extend tools such as Elasticsearch Rally, ClickBench, and vector search benchmark frameworks.
- Investigate performance differences through profiling, system metrics, and controlled experiments.
- Evaluate self-managed and managed cloud deployments, including serverless offerings, scaling behavior, and service constraints.
- Publish reproducible benchmark artifacts and technical reports with engineering and content partners.
- Partner with engineering and product management to turn performance 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 search, vector retrieval, analytical databases, or observability systems, with the ability to learn unfamiliar systems.
- Experience designing representative datasets and workloads involving query patterns, concurrency, and ingestion behavior.
- Sound experimental judgment involving repeated measurements, variability analysis, warm-up and cache effects, and measurement noise.
- 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 engineering recommendations.
- Preferred experience includes 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
- Base salary with no variable compensation component; the role is also currently eligible for Elastic's stock program.
- Company-matched 401k with dollar-for-dollar matching up to 6% of eligible earnings.
- Health coverage for employees and families in many locations.
- Distributed-company environment with flexible locations and schedules for many roles.
- Generous vacation days and up to 40 hours annually for volunteer projects.
- Matching of up to $2,000, or local-currency equivalent, for financial donations and service.
- At least 16 weeks of parental leave.
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.