SoC Low Power & Power Analysis Engineer

Arm is leading the vision to unlock a broad ecosystem of silicon required for AI, data centers, mobile, compute, and IoT! As part of the Solutions Engineering team, you will drive the development of advanced design methodologies, automation frameworks, and RTL integration strategies that enable scalable and high-quality SoC design. This role is ideal for experienced engineers passionate about front-end design automation, RTL integration, architectural exploration, and AI-assisted flows.

Job Overview:

We are seeking a SoC Low Power & Power Analysis Engineer with strong expertise in pre-silicon power estimation, sophisticated automation, and data-driven analysis. The ideal candidate will have hands-on experience with Synopsys PrimeTime/PrimePower, low-power signoff methodologies, machine learning–based estimation, and AWS-based ETL/analytics solutions. The role involves driving power reduction strategies, building automation frameworks, and collaborating multi-functionally with design, physical design, and verification teams.

Responsibilities:

Automation & Tool Development

• Architect and develop Python, Bash, and Tcl-based automation frameworks for power analysis, significantly reducing netlist-based power estimation turnaround times (e.g., 6 weeks → 2 weeks).
• Implement automated flows including complex script generation, LSF job scheduling, report parsing, and single-template configuration management.
• Build tools such as Excel-based power calculators for rapid early-stage power approximation and system-level modeling.

Data Engineering & Cloud Analytics

• Build and implement AWS-based ETL pipelines, aggregating simulation data into S3-based data lakes for centralized power analysis.
• Develop data extraction, normalization, and post-processing scripts in Python.
• Build dashboards using AWS QuickSight to provide project-wide access to power metrics, trends, and debugging insights.

Analytics driven Power Estimation (R&D)

• Develop machine-learning models for leakage prediction and early-stage power estimation, achieving 80–90% accuracy vs. signoff data.
• Drive proof-of-concept validation and influence future ML-enabled power prediction flows.

Required Skills and Experience :

• Bachelor’s or Master’s degree or equivalent experience in Electrical Engineering, Computer Engineering, or related field.
• 2+ years of confirmed experience in SoC low-power engineering, pre-silicon power estimation, signoff, or similar.
• Strong expertise in:
• Synopsys PTPX / PrimePower
• Low-Power Design Methodologies and Power Signoff
• Python, Tcl, Bash, Linux/Unix, LSF job scheduling
• AWS technologies: S3, ETL pipelines, QuickSight

“Nice To Have” Skills and Experience :

• Experience with machine learning model development and deployment for engineering workflows.
• Experience building enterprise-level dashboards or analytics tools.
• Publications in power systems, applied machine learning, or embedded systems.

In Return:

At Arm, we are proud to have a set of behaviors that reflect our culture and guide our decisions, defining how we work together to defy ordinary and shape extraordinary. These behaviors are assessed as part of the recruitment process:

• Partner and customer focus
• Teamwork and communication
• Creativity and innovation
• Team and personal development
• Impact and influence
• Deliver on your promises

We offer a hybrid approach to home and office working to provide an adaptable experience for all employees. We expect some working time to be spent in office, to promote a strong collaborative environment with good team integration but are accommodating to different home working requirements.

Our 10x mindset guides how we engineer, collaborate, and grow. Understand what it means and how to reflect 10x in your work:https://careers.arm.com/en/10x-mindset

#LI-RJ1

Accommodations at Arm

At Arm, we want to build extraordinary teams. If you need an adjustment or an accommodation during the recruitment process, please email accommodations@arm.com. To note, by sending us the requested information, you consent to its use by Arm to arrange for appropriate accommodations. All accommodation or adjustment requests will be treated with confidentiality, and information concerning these requests will only be disclosed as necessary to provide the accommodation. Although this is not an exhaustive list, examples of support include breaks between interviews, having documents read aloud, or office accessibility. Please email us about anything we can do to accommodate you during the recruitment process.

Hybrid Working at Arm

Arm’s approach to hybrid working is designed to create a working environment that supports both high performance and personal wellbeing. We believe in bringing people together face to face to enable us to work at pace, whilst recognizing the value of flexibility. Within that framework, we empower groups/teams to determine their own hybrid working patterns, depending on the work and the team’s needs. Details of what this means for each role will be shared upon application. In some cases, the flexibility we can offer is limited by local legal, regulatory, tax, or other considerations, and where this is the case, we will collaborate with you to find the best solution. Please talk to us to find out more about what this could look like for you.

Equal Opportunities at Arm

Arm is an equal opportunity employer, committed to providing an environment of mutual respect where equal opportunities are available to all applicants and colleagues. We are a diverse organization of dedicated and innovative individuals, and don’t discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.