Senior Verification Engineer

Job Overview:

Arm is using Machine Learning and Data Science techniques to empower verification teams to make data-driven decisions and is building automated workflows that enable our engineers to deliver more complex products.

We are looking for a creative and versatile senior verification engineer to join the "Machine Learning for Verification" (ML4V) team in Arm's Productivity Engineering group and deliver the full potential of ML4V across Arm engineering.

Responsibilities:

You will work directly with verification teams across engineering groups and product lines, embed the latest ML4V technologies into testbenches and project workflows, and improve the overall efficiency of verification.

This includes:

• Integrating ML4V into production environments, and optimising testbenches and workflows to maximise the benefits of deployment. This will include improving test generation and data visibility while ensuring that these changes continue to meet the project's verification goals.
• Supporting the evaluation of emerging ML technologies developed within Arm as well as those from EDA partners.
• Debugging ML4V issues, working in collaboration with ML4V Engineering and/or DevOps through to resolution, while also developing interim patches to ensure service continuity.
• Working with data scientists to identify and extract testbench data that could improve the ML models.
• Reporting on the overall ML4V user experience and project requirements (including future requirements) and feeding these into the ML4V roadmap.

Required Skills and Experience :

• Proficiency in a hardware verification language, preferably System Verilog/UVM, and developing coverage-driven constrained-random verification environments.
• Experience in all stages of the verification lifecycle for complex IP.
• Experience of interpreted scripting languages (ideally Python) or shell scripting.
• Strong communication skills.

“Nice To Have” Skills and Experience :

• Experience of high-level programming languages such as C/C++.
• Experience of EDA simulation, debug and coverage tools and using them in batch workflows.
• An understanding of machine-readable file formats, such as JSON.
• Experience of version control systems (e.g. Git) and continuous integration testing (e.g. using Jenkins).
• Knowledge of cloud computing services.