Top Tech Jobs & Startup Jobs in Montreal

Lead Elasticsearch search relevance and vector search initiatives. Design and implement search features, algorithms, and data structures; improve speed, relevance, and scalability; resolve complex bugs; and contribute to Lucene. Collaborate asynchronously with globally distributed engineers and open-source contributors, review code, guide technical direction, and write modern Java. Apply vector similarity techniques and algorithms such as HNSW or IVF on search platforms at scale.

Lead development of Elasticsearch search and vector-search capabilities, including designing algorithms and data structures, implementing new features, improving relevance and performance, fixing complex bugs, and contributing to Lucene. Collaborate autonomously with globally distributed engineers and open-source contributors, guide technical initiatives, review code, and use modern Java to build scalable search functionality.

Lead product strategy and roadmap for Elastic's Control Plane (orchestration and management) for Elastic Cloud. Partner with engineering, sales, and marketing to prioritize features, gather customer and market insights, and drive go-to-market. Focus on scalable orchestration, management, and developer-focused infrastructure capabilities while working asynchronously across distributed teams.

Develop and optimize Elasticsearch performance across distributed and serverless architectures. Build performance models, profiling and benchmarking workflows, regression detection, and AI-assisted optimization harnesses. Analyze bottlenecks in logging, metrics, vector search, and ES|QL; implement scalable, thread-safe, high-performance Java code; and collaborate across teams through technical reviews and guidance. Experience with JVM internals, distributed systems, performance engineering, and benchmarking is required.

Lead architectural and code-level performance engineering for Elasticsearch. Own major optimization initiatives, develop performance models, profile distributed systems, identify bottlenecks, build benchmarks and regression detection, and improve scalability across stateful and serverless architectures. Develop AI-assisted optimization and benchmarking harnesses, collaborate across teams, and mentor engineers. Work includes Java and JVM optimization, concurrency, distributed systems, vector search, storage engines, and native library integration.

Design, implement, and maintain Elasticsearch distributed-systems components to ensure scalable, performant, and resilient indexing, coordination, replication, and cluster communication. Diagnose and fix concurrency and performance issues, push scalability limits, and lead projects end-to-end while supporting support engineers and mentoring engineers across multi-node deployments.

Design, implement, and optimize Elasticsearch core storage and query engine components for logs/metrics workloads. Lead architecture, resolve performance bottlenecks, improve storage efficiency and query execution, mentor engineers, collaborate across distributed teams, triage community issues, and write idiomatic modern Java.

Drive architecture and design of Elasticsearch core storage and query engine for logs and metrics. Improve storage efficiency, indexing layouts, serialization, and performance; lead cross-team initiatives; mentor engineers; triage community issues; and write idiomatic modern Java.

Lead development of core Elasticsearch infrastructure and shared platform features. Design scalable APIs, solve performance and concurrency issues, improve observability and CI/CD, support cross-team projects, and own operational investigations end-to-end.

The Senior Java Developer will enhance Elasticsearch's distributed systems, maintain high performance, and solve complex problems related to data indexing and coordination across multiple machines.