DSP Systems Engineering (All Levels)

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. 

Your Team, Your Impact

Marvell’s CE DSP Architecture System Modeling team is expanding to support next-generation high-speed SerDes and D2D electrical interfaces operating up to 448 Gb/s per lane, including systems using higher-order PAM modulation. This is a high-impact engineering role where you will develop system-level DSP models, C/C++ algorithm prototypes, simulation frameworks, and silicon-correlation analysis that directly influence architecture, DSP/RTL design, validation, and customer applications. Ideal candidates excel in C/C++ DSP implementation, simulation-level debug, and producing reproducible, data-driven insight.

***We have multiple openings available, across levels. This position will be in San Diego, on-site. Compensation will be adjusted based on level.

What You Can Expect

• DSP & System-Level Modeling (C/C++)

  • Develop behavioral and functional models of key SerDes and D2D DSP blocks, including adaptation loops, timing recovery, and receiver signal processing functions.

  • Implement DSP algorithms and prototypes in C/C++, with Python for configuration, automation, and visualization.

  • Build parameterized system-level models to support architecture evaluation for SerDes up to 448G.

• Simulation-Level Debug & Analysis

• Perform simulation-level analysis across DSP, channel, and system blocks to isolate issues and unexpected behaviors.

  • Reproduce complex edge cases and support other DSP and RTL engineers with algorithm-level root-cause analysis.

  • Correlate silicon/lab observations with system-model predictions to accelerate debug and refinement.

• System and Channel Modeling

  • Integrate S-parameters, jitter/noise sources, device impairments, and IBIS-AMI elements into unified system simulations.

  • Support and expand scikit-rf-based and ADS-based TDR/TDT/SBR pipelines for channel characterization and documentation.

  • Evaluate higher-order PAM performance under real-world signal integrity constraints.

• Architecture & Cross-Functional Collaboration

  • Work closely with other DSP engineers to convert conceptual ideas and algorithmic approaches into executable C/C++ models.

  • Provide evidence-backed insights in early-phase development to de-risk DSP and RTL implementations.

• Silicon Bring-Up & Validation Support

  • Use system models to debug silicon performance gaps, timing issues, equalization behaviors, and adaptation anomalies.

  • Create simulation scenarios that mirror lab conditions to accelerate bring-up.

  • Provide validation and AE teams with modeling-based analysis and recommendations.

• Automation & Tool Development

  • Develop reusable C/C++ and Python modules for parameter sweeps, batch simulations, data pipelines, and visualization dashboards.

  • Contribute to Marvell’s world class internal system simulator, enabling reproducible modeling workflows across teams.

What We're Looking For

• M.S. or Ph.D. in Electrical Engineering, Computer Engineering, Applied Physics, or related field

• 2–12+ years of industry experience in DSP, high-speed communications, embedded firmware, or system modeling

• Strong C/C++ programming background with proven delivery in areas such as:

  • DSP algorithm implementation

  • Embedded/firmware or device-driver development

  • High-performance numerical code

• Strong debug skills across models, algorithms, and system layers

  • Solid understanding of DSP fundamentals, high-speed I/O concepts, and SerDes architectures up to 448G

• Proficiency in Python for modeling, automation, and analysis

  • Data aggregation and analysis with tools like Python pandas, and NumPy

• Experience correlating simulation results with lab/silicon measurements

• Able to work independently and as a team player in a fast-paced environment, with proactive tendencies, strong communication, and collaborative