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(www.enchargeai.com)
Principal Engineer, Static Timing Analysis (STA)
Location: Greater Bengaluru Area (Hybrid-2 days office/ 3days home)/Remote (Any where in India )
About Company:
EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge's robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today's best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems.
Role: Principal Engineer, Static Timing Analysis (STA)
We are looking for a visionary Principal Engineer to spearhead Encharge AI Timing leadership role.
This isn't just an execution role; we need a technical trailblazer who can navigate the complexities of advanced process nodes (2nm/3nm and beyond) while fostering a culture of innovation and rigorous critical thinking.
As the India Timing Lead, you will bridge the gap between architectural intent and silicon reality, ensuring our high-performance designs meet the most stringent timing, power, and reliability targets.
Key Responsibilities
Required Skills & Expertise
Category
Requirements
Core STA
Deep expertise in Signal Integrity (SI), Crosstalk, OCV/POCV/LVF, and Constraint Management (SDC).
Tooling
Mastery of Cadence Tempus (ECO, Tempus Stylus, and distributed timing).
Analysis
Proficiency in high-speed interface timing (DDR, PCIe) and low-power multi-voltage domains.
Scripting
Advanced Tcl/Python skills to automate complex flows and develop custom analysis tools.
Problem Solving
Proven ability to debug complex timing paths and offer creative ECO solutions that balance Power, Performance, and Area (PPA).
Mindset & Qualifications
Contact
Uday
[Confidential Information]
Mulya Technologies
Mining the Knowledge Community
Job ID: 144665687