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Drive the future of quality for the world’s most complex devices by building agentic workflows and intelligent frameworks. In this role, you will architect and develop tools that empower autonomous systems to assess, analyze, and enhance product quality at every stage. You’ll have unique opportunities to collaborate with machine learning experts and research teams, inventing new methodologies that proactively identify edge cases, surface actionable insights, and drive continuous improvement. Your work will set new standards for reliability, performance, and user experience across advanced hardware and software platforms.
Job Responsibility:
Design and build agentic testing frameworks that proactively identify quality issues and edge cases across complex hardware and software systems
Devise rigorous engineering and data-driven approaches for efficient training of AI models and algorithm implementation
Develop scalable, reusable tools and infrastructure that enable continuous quality analysis and improvement throughout the product lifecycle
Drive context engineering strategies to ensure robust internal quality workflows
Integrate the latest advances in machine learning and research into practical solutions that enhance product quality and reliability
Establish, track, and analyze key quality metrics to measure the effectiveness of agentic workflows and drive data-informed decision making
Automate quality assessment, reporting, and remediation processes to streamline and enhance quality workflows
Collaborate with research scientists and cross-functional partners in a team environment
Directly contribute to experiments, including designing experimental details, authoring reusable code, running evaluations, and organizing results
Mentor other team members and play a significant role in healthy cross-functional collaboration
Advocate for best practices in AI, software engineering, and quality to foster best engineering practices and innovation
Requirements:
Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
Experience with Python, C, C++, or other related programming languages, and with the PyTorch framework
3+ Years of experience in designing and developing applications that process and leverage large-scale datasets, with a focus on fine-tuning AI models and building agentic AI systems
Demonstrated ability to solve complex problems and compare alternative solutions, tradeoffs, and different perspectives to determine a path forward
Experience working and communicating cross-functionally in a team environment
Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment
Nice to have:
PhD in Computer Science, Computer Engineering, Machine Learning, or a related technical field
Experience with automated testing of consumer devices in a CI/CD environment
Expertise in leveraging AI/ML to optimize quality processes
Demonstrated ability to fine-tune and deploy advanced AI models for real-world QA scenarios
Familiarity with agentic AI systems for autonomous testing, computer use, and decision-making
Contributions to open source, industry standards, or published research in relevant fields
Experience with reinforcement learning, simulation environments, or agent-based modeling for quality assessment
Background in statistical analysis, experiment design, and evaluation methodologies for AI-driven quality systems
Familiarity with Reality Labs products, AR/VR devices, or other complex consumer hardware/software platforms