ML/AI Timing and Power Flow Expert

About Altera

At Altera, we are shaping the future of programmable logic by delivering high-performance, power-efficient FPGA solutions that enable innovation across cloud, communications, industrial, automotive, and AI-driven applications. Our teams push the boundaries of silicon design, verification, and implementation to deliver world-class products with exceptional quality of results (QoR).

We foster a culture of technical excellence, collaboration, and continuous innovation—empowering engineers to solve some of the industry’s most complex challenges while accelerating next-generation semiconductor technologies.

About the Role

We are seeking a highly skilled ML/AI Timing and Power Flow Expert with deep expertise in flow development, timing, power, library generation, and UPF-based methodologies, along with strong enthusiasm for applying ML/AI techniques to improve flow efficiency, debug productivity, and overall QoR.

In this role, you will architect and optimize advanced ASIC/FPGA implementation flows, focusing on timing and power convergence across full-chip and block-level designs. You will leverage machine learning and AI methodologies to enhance predictability, automate bottleneck analysis, and accelerate signoff closure. This is a highly visible, cross-functional position working closely with design, physical design, CAD, library, and reliability teams to enable best-in-class silicon performance and power efficiency.

Key Responsibilities

• Develop, enhance, and maintain robust timing and power flows across the physical design and signoff lifecycle.

• Own and drive STA flows, including timing setup, analysis, and timing collateral generation.

• Design and implement power-aware flows, including UPF integration, power intent validation, and comprehensive power/timing reporting.

• Lead standard-cell and macro library generation and characterization flows, including:

  • Timing, power, noise, and constraint characterization

  • Validation and quality checks for signoff readiness

  • Integration of characterized libraries into STA and power flows

• Build and maintain scalable, automated flow infrastructure using strong coding and software engineering practices.

• Apply ML/AI-driven approaches to:

  • Accelerate flow development and turnaround time

  • Improve debug efficiency for timing, power, library, and convergence issues

  • Enable smarter analysis, anomaly detection, and trend identification in timing, power, and library data

• Generate, analyze, and review timing, power, and library reports, ensuring accuracy, consistency, and signoff quality.

• Collaborate closely with PD, STA, library, power, and methodology teams to continuously improve flows and usability.

• Debug complex timing, power, library, and flow issues across multiple design stages and configurations.

• Bachelor’s Degree in Electrical Engineering, Computer Engineering, Computer Science, or related field with 8+ years of relevant industry experience in ASIC or FPGA timing/power/library flow development.

• 6+ years of experience in timing and power flow development and methodology.

• 6+ years of experience with industry-standard STA, power analysis, and library characterization tools.

• 6+ years of experience with excellent coding practices (Tcl, Python, Perl, or similar), focused on clean, reusable, and maintainable flow infrastructure.

• 6+ years of experience with deep understanding of timing concepts, STA methodologies, timing constraints, and timing collateral generation.

• 6+ years of experience in power analysis, optimization techniques, and comprehensive power reporting methodologies.

• 6+ years of hands-on experience with library generation and characterization, including timing, power, and noise model development and validation.

• 6+ years of experience working with UPF, including multi-power-domain designs and power intent modeling.

• 6+ years of experience in timing collateral generation, library integration into STA/power flows, and complex flow automation coding.

• Demonstrated ML/AI enthusiasm, with interest or experience in applying data-driven techniques to flow automation, debug, QoR prediction, or trend analysis.

• 5+ years of experience supporting advanced-node, large-scale, complex SoC designs (e.g., multi-million instance designs across multiple power domains).

• 3+ years of experience working with ML/AI frameworks, data analytics platforms, or statistical methods applied to EDA, timing/power analysis, or library characterization flows.

• 5+ years of experience performing deep data analysis and translating quantitative insights into measurable flow, timing, power, or library methodology improvements.

• 5+ years of demonstrated experience independently driving methodology enhancements end-to-end, from problem definition through deployment and production adoption.

• 5+ years of experience collaborating across cross-functional teams (PD, STA, library, CAD, power) with strong written and verbal technical communication skills.