QA Engineer

We are seeking a diligent and detail-oriented QA Engineer to join our R&D team. The successful candidate will be responsible for ensuring the quality and reliability of our model and core engines. You will play a key role in building testing infrastructure, benchmarking models, and defining complex data scenarios to predict how model performance impacts the final product.

Key Responsibilities:

• Test Automation Architecture:Design, develop, and optimize scalable automated testing frameworks for core engines. Focus on streamlining model benchmarking, regression suites, and performance profiling.
• Data Engineering for QA:Architect comprehensive data strategies. Define and synthesize complex data contexts and edge-case scenarios required to stress-test ML model robustness.
• End-to-End Risk Analysis:Evaluate model outputs through a product lens. Predict systemic risks and quantify how model variance impacts the final user experience post-integration.
• CI/CD Integration:Seamlessly integrate automated validation gates into the CI/CD pipeline to ensure continuous quality delivery for cloud-connected and embedded components.
• Cross-functional Collaboration:Work closely with Data and Dev teams to triage defects, analyze root causes, and refine model training requirements based on QA insights.

Design, develop, and optimize scalable automated testing frameworks for core engines. Focus on streamlining model benchmarking, regression suites, and performance profiling.

Architect comprehensive data strategies. Define and synthesize complex data contexts and edge-case scenarios required to stress-test ML model robustness.

Evaluate model outputs through a product lens. Predict systemic risks and quantify how model variance impacts the final user experience post-integration.

Seamlessly integrate automated validation gates into the CI/CD pipeline to ensure continuous quality delivery for cloud-connected and embedded components.

Work closely with Data and Dev teams to triage defects, analyze root causes, and refine model training requirements based on QA insights.

Basic Requirements

Technical Requirements

• Minimum 3 years in Software Quality Engineering or Backend Development, with a focus on automation.
• Bachelor’s degree in Computer Science, Machine Engineering, or a related technical field.
• Proficient inPython(for automation & ML scripting) andC++orJavaScript(for engine-level or web-integrated testing).
• Solid understanding ofAI/ML lifecyclesandComputer Visionfundamentals.
• Hands-on experience with cloud platforms (AWS, Azure, or GCP) and IoT/Robotics environments.
• Ability to calculate and interpret core metrics (mAP, Precision/Recall, F1-score, etc.) to assess model performance beyond simple "pass/fail" results.
• Proficiency with Git, Jira, TestRail, and modern CI/CD tools (Jenkins, GitLab CI, or GitHub Actions).

Minimum 3 years in Software Quality Engineering or Backend Development, with a focus on automation.

Bachelor’s degree in Computer Science, Machine Engineering, or a related technical field.

Proficient in (for automation & ML scripting) and or (for engine-level or web-integrated testing).

Solid understanding of and fundamentals.

Hands-on experience with cloud platforms (AWS, Azure, or GCP) and IoT/Robotics environments.

Ability to calculate and interpret core metrics (mAP, Precision/Recall, F1-score, etc.) to assess model performance beyond simple "pass/fail" results.

Proficiency with Git, Jira, TestRail, and modern CI/CD tools (Jenkins, GitLab CI, or GitHub Actions).

Preferred Qualifications

• Proactive Problem Solving:Proven track record of architecting test frameworks from scratch.
• Agile Proficiency:Experience in Scrum/Agile environments with a focus on rapid iteration.
• AI-Driven Productivity:Experience leveraging LLMs or AI-based coding assistants to accelerate test script generation and data synthesis.
• Communication:Ability to translate complex technical risks into actionable insights for non-technical stakeholders.

Proven track record of architecting test frameworks from scratch.

Experience in Scrum/Agile environments with a focus on rapid iteration.

Experience leveraging LLMs or AI-based coding assistants to accelerate test script generation and data synthesis.

Ability to translate complex technical risks into actionable insights for non-technical stakeholders.

Travel Requirements

Relocation Provided

Position Type

Referral Payment Plan

EEO Statement

Motorola Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion or belief, sex, sexual orientation, gender identity, national origin, disability, veteran status or any other legally-protectedcharacteristic.

We are proud of our people-first and community-focused culture, empowering every Motorolan to be their most authentic self and to do their best work to deliver on the promise of a safer world. If you’d like to join our team but feel that you don’t quite meet all of the preferred skills, we’d still love to hear why you think you’d be a great addition to our team.