Position Description The Tesla AI Hardware team is at the forefront of revolutionizing artificial intelligence through cutting-edge hardware innovation. Comprising brilliant engineers and visionaries, the team designs and develops advanced AI inference chips tailored to accelerate Tesla’s machine learning capabilities. A key part of this effort is Dojo, Tesla's custom supercomputer system built to efficiently train massive neural networks on vast video data from the fleet.

The work of Tesla's AI Hardware team powers the neural networks behind Full Self-Driving (FSD), and Tesla humanoid robot, Optimus, pushing the boundaries of computational efficiency and performance. By creating custom silicon and optimized architectures, the team ensures Tesla remains a leader in AI-driven automotive and energy solutions, shaping a future where intelligent machines enhance human life. Tesla's AI Hardware Team is looking for experienced, highly skilled VLSI engineers who enjoy working across the logic, circuit, methodology, and physical design levels.

Our physical design team is growing to tackle a wider range of projects, building on our in-house SOC design expertise. This position entails the design, construction and integration of SOCs, IP, circuits, tool flows, and methodologies into systems using advanced technologies - from definition through characterization. Our AI Hardware engineering team implements world-class clocking for high-performance SoCs where skew directly impacts chip performance.

As a Sr.

Clock Distribution

Engineer, you will own the physical implementation of clock distribution networks — designing H-trees, driving floorplan-stage clock planning in Innovus, and pushing skew to the limits of what the process allows. Your work bridges clock architecture intent and physical reality.

Responsibilities Design and implement H-tree clock distribution networks — plan topology, trunk routing,



and branch balancing to minimize skew across the full clock domain Own clock planning at the floorplan stage in Innovus — place clock roots, define clock trunk paths, and establish pre-CTS constraints that guide downstream implementation Drive skew optimization from floorplan through CTS closure — iterate on H-tree structure, buffer placement, and load balancing to meet skew targets Size clock drivers and buffers — analyze drive strength requirements and validate EMIR compliance for large clock drivers under peak switching current conditions Evaluate EM and IR impact of high-fanout clock networks — ensure clock trunk and driver sizing meets electromigration current density limits and IR drop budgets Develop CTS constraints and guidelines — define skew groups, clock latency targets, and insertion delay budgets for the CTS engine Validate clock distribution against post-route parasitics — analyze skew degradation and drive ECO fixes to recover timing Implement clock shielding strategies to protect clock trunks from aggressor coupling and noise Analyze and optimize clock power — balance transition times, driver strengths, and switching activity for power efficiency Leverage agentic AI flows to automate H-tree generation, skew analysis, and EMIR validation across clock domains Requirements Degree in Electrical Engineering, Computer Engineering, or related field, or equivalent work experience 7+ years of clock distribution implementation experience on high-performance SoCs Deep expertise in H-tree clock topology design and skew optimization Hands-on proficiency with Innovus for floorplan-stage clock planning and CTS implementation Robust understanding of EMIR concepts as applied to large clock drivers and high-fanout clock networks Experience sizing clock drivers for EM compliance under peak switching conditions Solid grasp of pre-CTS planning, CTS constraints, and post-route skew validation Ability to use agentic AI flows to automate clock distribution analysis and optimization

📌 Sr. Clock Distribution Engineer, AI Hardware (Bengaluru)
🏢 Tesla
📍 Bengaluru