Staff SOC Static Timing Analysis Engineer – Dojo
Company | Tesla |
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Location | Palo Alto, CA, USA |
Salary | $Not Provided – $Not Provided |
Type | Full-Time |
Degrees | Bachelor’s |
Experience Level | Senior |
Requirements
- Bachelor’s degree in a related field, or equivalent experience
- Proven track record of successful tape-outs and meeting performance targets
- Strong understanding of micro-architecture and physical design concepts
- Proficient in using industry-standard EDA tools for STA, such as PrimeTime, Tempus, or equivalent
- Familiarity with scripting languages such as Tcl or Perl for automation
Responsibilities
- Perform static timing analysis and optimization to ensure design closure and meet performance requirements
- Collaborate with the design and physical implementation teams to develop timing constraints and methodologies for achieving optimal performance
- Conduct feasibility studies to evaluate design trade-offs and propose solutions to improve timing and power
- Identify and resolve timing issues, including setup and hold violations, clock domain crossing, and other timing-related problems
- Work closely with the verification team to analyze and resolve timing-related functional issues
- Develop and maintain timing models and libraries for accurate and efficient timing analysis
- Drive and support STA-related methodologies, flows, and tool enhancements to improve productivity and quality of results
- Stay up to date with the latest industry trends and best practices in STA and related fields
- Understanding of ECO flows and eco generation methodologies
- Experience with timing constraints development and validation
Preferred Qualifications
- Experience with advanced process technologies (e.g., FinFET, 7nm, 5nm) is preferred
- Knowledge of low-power design techniques and clock domain crossing analysis is preferred
- Familiarity with formal verification techniques and tools is preferred
- Experience with high-speed interface protocols (e.g., PCIe, DDR, Ethernet) is preferred
- Understanding of statistical timing analysis and variation-aware design methodologies is preferred