Meta
Software Engineer, HW/SW Co-Design
$154K–$217K
Bellevue, WA +2 · Full-time · Posted Oct 7, 2026
- Location
- Bellevue, WA
Menlo Park, CA
New York, NY - Experience
- 5+ years with programming and scripting languages; 5+ years with hardware architecture, compute technologies and/or storage systems; 3 years in technical leadership (stated as a qualification).
- Education
- Bachelor’s degree in Computer Science, Computer Engineering, or a relevant technical field, or equivalent practical experience; also states Bachelor’s degree in Computer Science or equivalent technical experience.
About the job
Defines and advances compute and storage architectures for Meta’s infrastructure through workload analysis, hardware/software co-design, benchmarking, and collaboration with engineering teams and industry partners.
What you'll do
- Analyze fleet workloads and hardware bottlenecks, and work with software teams to improve performance and reduce resource use.
- Build representative benchmarks and evaluate platforms; identify co-design opportunities and define technology roadmaps.
- Influence vendor roadmaps and partner with engineering teams to bring hardware capabilities into production.
What they ask for
- Bachelor’s degree in Computer Science, Computer Engineering, or a relevant technical field, or equivalent practical experience.
- 5+ years of experience with programming and scripting languages such as C, C++, Rust, Java, PHP, Python.
- Experience with large-scale infrastructure, distributed systems, and full-stack analysis of server applications.
- 5+ years of experience with hardware architecture, compute technologies and/or storage systems.
Nice to have
- Master’s degree or PhD in Computer Science or a related technical field.
- 3 years of experience in a technical leadership role, leading projects, driving technical direction, and mentoring.
Pay
$154,003/year to $217,000/year USD (base salary)
Tools
C, C++, Rust, Java, PHP, Python, Hack, Spark
AI focus
Includes AI training and AI-related distributed systems work; requires responsible, ethical AI practices, ongoing AI skill development, and use of AI tools to improve workflows.
Model-written summary · the original posting is authoritative