Software Engineering LMTS
$149k - $260k • Remote • California - San Francisco
Posted 1d ago
Job Location
California - San Francisco
Tech Stack
Remote Work Policy
Fully remote
Categories
Machine Learning Engineer
About the job
Salesforce is seeking a Senior/Lead Performance Engineer to join the SalesforceDB team, which manages the transactional database powering the Salesforce Platform. This role involves driving the design, scalability, and performance of our distributed database technology. You will identify and resolve performance bottlenecks, lead benchmarking efforts, and build telemetry to monitor production fleet performance. This is a fast-paced, collaborative environment where your work directly impacts the performance and scalability of a system handling trillions of transactions monthly.
Responsibilities
- Drive the design and scalability of the database stack in partnership with development teams.
- Identify optimization opportunities by profiling the database engine and storage service.
- Determine the root cause of performance and scalability issues and drive resolutions.
- Lead benchmarking and modeling to inform hardware selection and capacity planning.
- Build telemetry, dashboards, and analysis to track production fleet performance against targets.
- Own the performance qualification of SalesforceDB releases, including running workloads and benchmarks.
Requirements
- Related technical degree or equivalent experience.
- 5+ years of performance engineering experience on systems software, preferably databases, storage, or distributed systems.
- Strong computer science fundamentals including data structures, algorithms, concurrency, and memory management.
- Proficiency in Java or C/C++.
- Practical experience with load, benchmark, and regression testing, especially for large-scale multi-tenant workloads.
- Proven track record of root cause analysis for performance and scalability problems in complex distributed systems.
- Strong SQL and performance data analysis skills (CPU, latency, throughput, per-tenant resource use).
- Experience with telemetry, dashboards, and monitoring against performance targets.
- Fluency with Linux, OS internals, and shell/Python scripting.
- Clear communication and collaboration skills across various engineering teams.
- Integrity and a growth mindset.