Staff Engineer Engineering Compute Infrastructure and Grid Operations
About Marvell
Marvell’s semiconductor solutions are the essential building blocks of the data infrastructure that connects our world. Across enterprise, cloud and AI, and carrier architectures, our innovative technology is enabling new possibilities. At Marvell, you can affect the arc of individual lives, lift the trajectory of entire industries, and fuel the transformative potential of tomorrow. For those looking to make their mark on purposeful and enduring innovation, above and beyond fleeting trends, Marvell is a place to thrive, learn, and lead.
Job Summary
We are seeking a Senior Engineer to design, operate, and continuously improve the engineering compute infrastructure used for large-scale chip design and verification. This role is heavily focused on grid job management, storage systems, reliability, and operational excellence in high-throughput compute environments. The ideal candidate has strong IT and systems skills, deep experience with batch schedulers and distributed storage, and a passion for diagnosing and preventing large-scale job failures that impact engineering productivity.
Key Responsibilities
Own and evolve grid job management infrastructure used for large regressions and high-volume batch workloads.
Debug and resolve grid job failures, including scheduling issues, hung jobs, resource starvation, and intermittent infrastructure faults.
Improve job reliability through watchdogs, retries, heartbeats, timeouts, and failure detection mechanisms.
Work with job controllers and wrapper layers to ensure consistent behavior across grid environments (e.g., LSF, UGE).
Partner with IT and compute teams during grid migrations, upgrades, and expansions.
Qualifications and Skills
Bachelor’s degree in computer science, Computer Engineering, Electrical Engineering, or equivalent experience.
8+ years of experience in compute infrastructure, grid operations, or large-scale engineering environments.
Strong experience with grid or batch schedulers (e.g., LSF, UGE, Slurm, PBS).
Hands-on experience debugging distributed systems and batch job failures.
Strong Linux systems knowledge, including process management and resource monitoring.
Experience with shared storage systems (NFS, enterprise filers, high-performance filesystems).
Strong scripting skills in Python, shell, or similar languages.
Preferred Qualifications
Experience supporting EDA or engineering compute workloads.
Familiarity with job controller or wrapper-based execution architectures.
Experience operating environments with thousands of concurrent batch jobs.
Exposure to cloud or hybrid compute environments.
Prior involvement in grid or filesystem migrations.
Strong incident response and post-mortem leadership skills.
Expected Base Pay Range (USD)
$128,000 - $189,370, $ per annum
Additional Compensation and Benefit Elements
Marvell is committed to providing exceptional, comprehensive benefits that support our employees at every stage - from internship to retirement and through life’s most important moments. Our offerings are built around four key pillars: financial well-being, family support, mental and physical health, and recognition. Highlights include an employee stock purchase plan with a 2-year look back, family support programs to help balance work and home life, robust mental health resources to prioritize emotional well-being, and a recognition and service awards to celebrate contributions and milestones.
Interview Integrity
To support fair and authentic hiring practices, candidates are not permitted to use AI tools (such as transcription apps, real-time answer generators like ChatGPT or Copilot, or automated note-taking bots) during interviews. These tools must not be used to record, assist with, or enhance responses in any way. Our interviews are designed to evaluate your individual experience, thought process, and communication skills in real time. Use of AI tools without prior instruction from the interviewer will result in disqualification from the hiring process.