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Staff Engineer, SSD Hardware PCIE

Job in Longmont, Boulder County, Colorado, 80502, USA
Listing for: 1000 Micron Technology, Inc.
Full Time position
Listed on 2026-10-02
Job specializations:
  • Engineering
    Test Engineer, Hardware Engineer, Systems Engineer
Salary/Wage Range or Industry Benchmark: 146000 - 297000 USD Yearly USD 146000.00 297000.00 YEAR
Job Description & How to Apply Below
Micron Technology

Our vision is to transform how the world uses information to enrich life for all. Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever.

Job Description

Join Micron’s SSD Hardware Architecture organization, where we develop the technologies that power next-generation storage solutions. We work across architecture, silicon, firmware, and product engineering teams to deliver high-performance SSD controllers that meet demanding standards for quality, reliability, and innovation. As a Staff SSD Hardware PCIe Engineer, you will play a key role in bringing advanced SSD controller technologies to life.

This position offers the opportunity to lead PCIe subsystem validation, debug complex system-level challenges, and influence future product capabilities while collaborating with highly skilled engineering teams across the organization.

Responsibilities
  • Develop hardware and system specifications from architectural and product requirements
  • Lead PCIe bring-up, characterization, debugging, validation, and compliance activities for SSD controller So Cs
  • Partner with architecture, verification, firmware, product engineering, and external IP vendors to resolve issues and improve functionality
  • Drive system-level validation methodologies, automation, and test development to improve coverage and efficiency
  • Perform root-cause analysis and validate PCIe functionality across complex SSD use cases
Minimum Qualifications
  • Bachelor’s degree in Electrical Engineering, Computer Engineering, Electronics Engineering, or a related field, or equivalent experience
  • Proven experience in hardware development, silicon validation, PCIe subsystem engineering, or related areas
  • Strong expertise with PCIe Gen4, Gen5, and/or Gen6, PCIe host systems, root complexes, PCIe IP bring-up, validation, compliance, and interoperability testing
  • Extensive knowledge of PCIe LTSSM and post-silicon validation and debug methodologies
  • Proficiency in Python, TCL, C, or similar scripting and programming languages, along with experience using high-speed test and measurement equipment
Preferred Qualifications
  • Experience implementing or validating PCIe subsystems in ASIC and/or FPGA environments
  • Knowledge of SSD controller architectures, storage systems, and SoC integration or validation
  • Understanding of PCIe link equalization, DFE, receiver architectures, signal integrity, and power integrity concepts
  • Experience solving complex high-speed hardware, PCB, and Ser Des-related challenges
  • Master’s degree in Electrical Engineering or a related field, and experience employing AI tools such as Claude Code to create or verify code and improve validation efficiency
AI & Intelligent Systems

As part of Micron’s ongoing digital transformation, this role includes a strong expectation that engineers bring (or actively develop) capabilities in AI-enabled software development, including:

  • Practical experience or solid grounding in integrating AI/ML capabilities into applications, including employing large language models (LLMs) and sophisticated inference services
  • Familiarity with agentic architectures - designing and orchestrating autonomous or semi-autonomous software agents that can reason, plan, and implement multi-step workflows
  • Experience building or integrating workflows that use advanced technology techniques, such as task decomposition, tool chaining, retrieval-augmented generation (RAG), and context-aware decision systems
  • Understanding of responsible AI principles, including model evaluation, observability, and safe deployment practices
  • Ability to find opportunities where AI and automation can…
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