Company

Qualcomm India Private Limited

Job Area

Engineering Group, Engineering Group > Machine Learning Engineering

General Summary

As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Machine Learning Engineer, you will create and implement machine learning techniques, frameworks, and tools that enable the efficient discovery and utilization of state-of-the-art machine learning solutions over a broad set of technology verticals or designs. Qualcomm Engineers collaborate with cross-functional teams to enhance the world of mobile, edge, auto, and IOT products through machine learning hardware and software.

Minimum Qualifications

Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 4+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

OR

Master's degree in Computer Science, Engineering, Information Systems, or related field and 3+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

OR

PhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

Staff – Application/ Customer Engineering

Role Overview

We are looking for a Staff Engineer with strong domain expertise in VLSI/EDA tools and workflows to drive adoption, usability, and reliability of internal GenAI/Agentic AI tools and platform.

This role requires deep hands-on usage, triaging expertise, and customer engineering experience, acting as the bridge between Physical Design Engineers/CAD teams, Software and Systems engineering team.

The ideal candidate has exposure to AI/GenAI systems and can understand and debug workflows involving EDA tools, AI agents, orchestration pipelines, and non-deterministic system behaviors.

Key Responsibilities

Own end-to-end user support and triage workflows; debug complex EDA environment, configuration and software integration issues
Diagnose workflow failures across toolchains, configurations, and infrastructure
Drive deep product understanding through hands-on tool usage across real workflows
Translate user requirements and issues into clear, actionable engineering inputs
Configure and onboard new projects and users; enable scalable adoption
Define and maintain real-world test cases and reproducible debugging scenarios
Collaborate with dev/QA teams to improve observability, debuggability, and stability
Debug AI/GenAI agent workflows, including orchestration failures, tool invocation issues, and non-deterministic behavior
Ensure tools operate in an agentic model with autonomous execution (MCP-based access) and minimal manual intervention
Define and validate clear functional specifications covering capabilities, inputs, outputs, and expected behavior
Drive structured enablement plans with phased onboarding, deliverables, acceptance criteria, and timelines
Develop comprehensive test strategies including shared and hidden testcases for robust validation
Measure tool performance using objective QoR metrics (TNS, WNS, congestion, runtime, memory)
Integrate tools into automated validation/regression pipelines for continuous testing and reporting
Enable usage telemetry collection (feature usage, runtime distribution, error trends) to support data-driven improvements

Required Skills & Experience

9-12 years in Applications Engineering / Customer Engineering preferably in Physical Design (PNR/Floor planning)
Strong domain knowledge in VLSI / Physical Design / EDA workflows
Knowledge of Agentic AI /MCP/RAG workflows
Proven expertise in triaging and debugging complex software/tool issues
Strong Python/Linux/scripting experience
Ability to independently run and debug end-to-end workflows
Strong problem decomposition and root-cause analysis skills
Excellent communication and cross-functional collaboration

Preferred Qualifications

Experience with AI/GenAI tools, agent frameworks, or orchestration systems
Familiarity with evaluation, benchmarking, or validation pipelines
Exposure to CI/CD, large-scale systems and HPC environments
Experience improving workflows, UX, or developer productivity

Positioning

This is a hands-on Applications / Customer Engineering role with strong domain expertise, triage ownership, and AI/GenAI workflow understanding — not a Product Manager role.

Applicants: Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail [HIDDEN TEXT] or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).

Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.

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If you would like more information about this role, please contact Qualcomm Careers.

Staff Engineer- EDA ML Tools - Customer Engineering(Physical Design)