Micron
MTS Firmware Engineer
$175K–$307K
Longmont-MAX- Office, CO · Full-time · Posted Sep 18, 2026
- Experience
- 7+ years in embedded firmware development; 3+ years in the SSD industry.
- Education
- Bachelor's degree in Computer Engineering, Electrical Engineering, Computer Science, or a related technical field.
About the job
Defines the architecture and long-term strategy for Common Services firmware across SSD products, leading engineering decisions and collaboration across hardware, silicon, systems, and software.
What you'll do
- Define and evolve Common Services firmware architecture and technical strategy across SSD products and storage platforms.
- Lead embedded firmware design, set engineering standards, and address system-level challenges with cross-functional teams.
- Mentor engineers and lead adoption of AI-assisted development practices.
What they ask for
- Bachelor's degree in Computer Engineering, Electrical Engineering, Computer Science, or a related technical field.
- 7+ years of embedded firmware development experience with architectural ownership and technical leadership in the storage or semiconductor industry.
- 3+ years of SSD industry experience with expertise in Common Services firmware, ARC processors, compilers, and build environments.
- Expert-level proficiency in C and/or Rust, deep knowledge of PCIe/NVMe storage architectures, and experience delivering solutions across hardware, silicon, system software, and product teams.
Nice to have
- Experience with RISC-V processors, Python-based automation, and embedded systems spanning hardware through application layers.
- Experience with firmware performance analysis, optimization, benchmarking, system-level debugging, or applying AI and machine learning to engineering or product outcomes.
Pay
$175,000.00 - $307,000.00 a year (USD, base salary)
Tools
C, Rust, PCIe/NVMe, ARC processors, compilers, build environments, RISC-V, Python
AI focus
Leads adoption of AI-assisted development practices; preferred experience evaluating and applying AI and machine learning to improve engineering productivity, product quality, or product capabilities.
Model-written summary · the original posting is authoritative