Responsibilities
- Create machine learning-driven solutions and workflows to enhance performance, power efficiency, area utilization, and implementation speed across chip development stages from synthesis to tapeout for multiple IP blocks.
- Collaborate with physical design engineers to build ML-powered tools targeting synthesis, place and route, timing closure, and power distribution network analysis.
- Identify and source suitable datasets, choose effective data encoding strategies, and develop novel algorithmic approaches.
- Conduct machine learning experiments, evaluate outcomes with statistical methods, and refine models based on empirical results.
Compensation
Between $50 and $70 per hour, inclusive of base and variable components
Work Arrangement
On-site — Santa Clara, CA, Austin, TX
Other
- This position requires on-site presence with a 40-hour workweek in either Santa Clara, California or Austin, Texas.
- Intern compensation ranges from $50 to $70 per hour, combining base and variable pay targets.
- Final compensation offers are influenced by individual experience, technical skills, educational background, and location.
- In compliance with U.S. Export Control regulations, the company must adhere to licensing requirements when transferring technology to individuals from certain countries.
- Proof of citizenship, permanent residency, asylum status, or refugee status may be required during the hiring process.
- Employment cannot commence until a U.S. export license with acceptable terms is approved by the relevant authorities, if required.
- Should the U.S. government deny a necessary export license under acceptable conditions, the job offer will be withdrawn.
- Offer validity depends on the candidate’s eligibility to access U.S. export-controlled technology.
