UX Engineer, Data Collection, Extended Reality, AI

📍 Job Overview

Job Title: UX Engineer, Data Collection, Extended Reality, AI

Company: Google

Location: San Jose, California, United States

Job Type: Full-Time

Category: User Experience Engineering / Extended Reality Operations

Date Posted: 2025-09-11T06:31:20.444

Experience Level: 5-10 Years

Remote Status: On-site

🚀 Role Summary

• This role focuses on the intersection of User Experience (UX) Engineering, data collection strategies, and the burgeoning fields of Extended Reality (XR) and Artificial Intelligence (AI).

• Responsibilities include interfacing with hardware APIs and remote procedure calls (gRPC) for seamless device communication, and working directly with both consumer and prototype hardware.

• A key aspect involves collaborating with hardware and UX teams to design and implement intuitive software solutions, shaping the user experience of cutting-edge XR applications.

• The position requires strong front-end development skills, coupled with experience in server-side development and API integration, particularly within the XR and AI ecosystem.

• This role is crucial for developing foundational models and core technology that will power future machine learning advancements and unlock next-generation user experiences by creating digital versions of reality.

📝 Enhancement Note: While the job title is "UX Engineer," the responsibilities and required skills, particularly around data collection for AI and XR, place this role within the broader operational and technical execution sphere of GTM and product development. The emphasis on interfacing with hardware and creating digital realities suggests a deep involvement in the data pipeline and user experience infrastructure that underpins AI and XR product success.

📈 Primary Responsibilities

• Interface seamlessly with public and experimental hardware APIs, as well as Remote Procedure Calls (gRPC) services, to ensure robust and efficient device communication for data collection.

• Engage directly with a variety of hardware, ranging from readily available consumer devices to highly specialized, custom-built prototypes, to facilitate data acquisition.

• Collaborate closely with the dedicated hardware engineering team to conceptualize, develop, and implement intuitive and user-friendly software solutions that support XR data collection and AI model training.

• Function as a UX Engineer, focusing on building exceptionally user-friendly interfaces and critically shaping the overall user experience for advanced software applications within the XR domain.

• Partner with other engineers throughout the development lifecycle, contributing to final implementation, refinement, and polishing of software features and user interfaces.

• Contribute to the development of foundational models and core technologies essential for powering the future of machine learning and accelerating product development within the XR and AI space.

• Drive the creation of digital versions of reality, thereby reducing dependency on real-world data for AI model development and validation.

📝 Enhancement Note: The primary responsibilities highlight a blend of technical implementation, cross-functional collaboration, and direct contribution to AI/XR product development. The emphasis on "data collection," "digital versions of reality," and "interfacing with hardware APIs" strongly indicates a role focused on the operational backbone of AI/XR product innovation, aligning with GTM and product operations functions.

🎓 Skills & Qualifications

Education:

Experience:

• A minimum of 4 years of hands-on experience in front-end development, demonstrating proficiency in core web technologies such as JavaScript, HTML5, and CSS.

• Proven experience in application development across at least one platform or area, including web, iOS, Android, Computational Design (CompDes), or Extended Reality (XR).

• Demonstrated experience with server-side development, specifically utilizing Node.js and working with APIs to build robust backend functionalities.

Required Skills:

• Front-End Development: Deep expertise in JavaScript, HTML5, and CSS for building dynamic and responsive user interfaces.

• Server-Side Development: Proficiency in Node.js for backend logic, API development, and managing server-side operations.

• API Integration: Strong understanding and practical experience in integrating with various APIs, including RESTful services and potentially gRPC.

• Extended Reality (XR) Fundamentals: Foundational knowledge and practical experience with AR, VR, or Extended Reality concepts and development principles.

• User Interface (UI) Design Principles: Ability to translate design concepts into functional, user-friendly interfaces and contribute to shaping the overall user experience.

Preferred Skills:

• Hardware Interfacing: Experience in software development that interfaces directly with hardware devices, such as cameras, sensors, or other peripherals.

• Android Development: Familiarity with Android device development and the Android ecosystem.

• XR/AR/VR Development Platforms: Experience with development platforms or frameworks specific to augmented reality, virtual reality, or extended reality (e.g., Unity, Unreal Engine).

• Relational Databases: Experience with relational database management systems like SQLite, PostgreSQL, or Google Cloud Spanner.

• Unity & C#: Proficiency in Unity game engine and C# programming for XR application development.

• Smart Home Device Integration: Experience integrating software solutions with smart home devices and their respective APIs.

• JavaScript Frameworks: Knowledge of modern JavaScript frameworks such as Vue.js, React, or Angular.

• Data Collection & Management: Understanding of data collection methodologies, data pipelines, and efficient data management practices, particularly for AI/ML training.

📝 Enhancement Note: The qualifications emphasize a blend of core software engineering principles with specialized knowledge in XR and AI data collection. The distinction between minimum and preferred qualifications points towards a need for strong foundational development skills, with a clear preference for candidates who have prior exposure to hardware interaction, XR environments, and data-centric development for AI.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Demonstrated UI/UX Implementation: Showcase examples of user interfaces you have designed and built, highlighting usability, interactivity, and adherence to UX best practices. Focus on how your interface designs enhance user workflows and data capture efficiency.

• XR/AR/VR Project Showcase: Include projects that demonstrate your experience with Extended Reality technologies, such as AR/VR application development, 3D asset integration, or spatial computing interactions.

• API Integration Examples: Provide evidence of successful API integrations, illustrating how you've connected different systems or services to create cohesive functionalities, particularly for data flow or device communication.

• Server-Side Logic & Data Handling: Present projects that involve server-side development (e.g., Node.js) where you managed data processing, business logic, or backend services relevant to data collection or application functionality.

• Hardware Interaction Showcase: If possible, include projects or descriptions of how you've developed software to interact with hardware devices, demonstrating your ability to bridge the physical and digital realms for data acquisition or control.

Process Documentation:

• Workflow Design & Optimization: Document a process you've designed or optimized for data collection, user interaction, or system integration. Explain the problem, your solution, and the efficiency gains achieved.

• System Implementation & Integration: Detail a project where you implemented or integrated software systems, outlining the architecture, key technologies used, and how the integration facilitated data flow or improved operational efficiency.

• Performance Analysis & Measurement: For your showcased projects, include metrics related to performance, efficiency, user engagement, or data accuracy. Demonstrate how you measured and analyzed the success of your operational contributions.

📝 Enhancement Note: For a role involving XR, AI data collection, and hardware interfacing, a portfolio should not only showcase finished products but also the underlying technical processes and systemic thinking. Demonstrating an ability to manage complex data pipelines, integrate diverse systems, and optimize workflows for efficiency and accuracy will be critical.

💵 Compensation & Benefits

Salary Range:

• The US base salary range for this full-time position is $129,000 - $185,000 annually.

Benefits:

• Bonus: Eligibility for performance-based bonuses, rewarding contributions to team and company goals.

• Equity: Potential for stock options or grants, providing ownership and participation in Google's growth.

• Comprehensive Benefits Package: Includes health insurance (medical, dental, vision), retirement savings plans (e.g., 401k with company match), paid time off, parental leave, life insurance, and disability coverage.

• Professional Development: Access to learning resources, training programs, and opportunities for skill enhancement relevant to AI, XR, and software engineering.

• Wellness Programs: Support for employee well-being through various health and wellness initiatives.

Working Hours:

• Standard full-time working hours are expected, typically around 40 hours per week.

• While the role is on-site, Google often fosters a flexible work environment within office hours, allowing for efficient workflow management and task completion.

📝 Enhancement Note: The provided salary range is competitive for a UX Engineer role with specialized skills in AI and XR in the San Jose, CA area. The inclusion of bonus and equity signifies a performance-driven culture, common in tech companies like Google. The benefits package is robust, reflecting Google's commitment to employee well-being and professional growth.

🎯 Team & Company Context

🏢 Company Culture

Industry: Technology (Software, AI, Extended Reality, Hardware Integration)

Company Size: Google is a massive global technology corporation, employing hundreds of thousands of individuals worldwide. This vast scale offers extensive resources, diverse projects, and a wide array of career paths.

Founded: 1998. Google's history is marked by innovation, a user-centric philosophy, and a relentless pursuit of organizing the world's information and making it universally accessible and useful. This ethos permeates its approach to new technologies like AI and XR.

Team Structure:

• Cross-Functional Collaboration: The UX team at Google is inherently multi-disciplinary, comprising UX Designers, Researchers, Writers, Content Strategists, Program Managers, and Engineers. This role will operate within such a collaborative environment.

• Specialization Areas: Within the broader XR team, there are likely specializations in hardware development, software engineering, AI/ML research, data collection, and user experience design. This role bridges software engineering with XR and AI data needs.

• Reporting Structure: UX Engineers typically report into a UX lead or Engineering Manager, working closely with Product Managers and Design leads on specific product initiatives. The structure emphasizes collaboration and shared ownership of product outcomes.

Methodology:

• Data-Driven Decision Making: Google's operations and product development are heavily reliant on data analysis and user insights to inform design choices, feature prioritization, and strategic direction.

• Agile & Iterative Development: Projects often follow agile methodologies, involving iterative cycles of design, prototyping, testing, and refinement to ensure continuous improvement and rapid adaptation to user feedback and technological advancements.

• User-Centric Design: The core philosophy of "Focus on the user and all else will follow" is deeply embedded, guiding all aspects of product creation and operational processes to meet user needs and expectations.

Company Website: https://www.google.com

📝 Enhancement Note: Google's culture is renowned for its innovation, data-driven approach, and emphasis on user experience. For an XR/AI UX Engineer, this means working in a dynamic environment with cutting-edge technology, high collaboration, and a strong focus on transforming user interactions through AI and immersive technologies. The scale of Google provides unparalleled opportunities for impact and learning.

📈 Career & Growth Analysis

Operations Career Level: This position is likely at an intermediate to senior level within the UX Engineering discipline, requiring a solid foundation in front-end development and specialized experience in XR and AI data collection. It's a role that bridges core engineering with the operational aspects of building AI-powered XR experiences.

Reporting Structure: The UX Engineer will typically report to a UX Engineering Manager or a Senior Lead within the XR or AI division. They will work collaboratively with cross-functional teams, including UX Designers, Researchers, Product Managers, and AI/ML Engineers, often in a matrixed reporting structure for project-specific tasks.

Operations Impact: This role directly impacts the operational efficiency and effectiveness of AI model development and XR product launches. By ensuring seamless data collection and contributing to intuitive user interfaces, the UX Engineer plays a critical role in accelerating product cycles, improving data quality, and enhancing the overall user experience, which are key drivers of GTM success.

Growth Opportunities:

• Specialization in AI/XR: Deepen expertise in AI and Extended Reality technologies, becoming a subject matter expert in data collection, immersive interface design, and hardware-software integration for next-generation computing.

• Technical Leadership: Progress into senior engineering roles, technical lead positions, or management roles within UX engineering, data science, or XR product teams.

• Cross-Disciplinary Skill Development: Expand skills into areas like AI/ML model development, advanced 3D graphics programming, or hardware prototyping through internal projects and training.

• Product Ownership: Take on greater ownership of specific features or product areas, driving strategic technical decisions and contributing to product roadmaps.

• Mentorship: Mentor junior engineers and contribute to the growth of the UX engineering community within Google.

📝 Enhancement Note: The career path for a UX Engineer at Google, especially in emerging fields like AI and XR, offers significant growth potential. The role provides a strong foundation for specialization and leadership in high-impact technological areas, allowing for both technical depth and strategic career progression.

🌐 Work Environment

Office Type: This is an on-site role based at Google's facilities in San Jose, California. Google offices are known for their innovative design, collaborative spaces, and comprehensive amenities aimed at fostering productivity and employee well-being.

Office Location(s): San Jose, California, USA. This location is part of Silicon Valley, a hub for technology innovation, offering access to a vibrant ecosystem of tech companies, talent, and resources.

Workspace Context:

• Collaborative Hubs: Expect open-plan work areas, meeting rooms equipped with advanced AV technology, and dedicated project spaces designed to facilitate seamless collaboration with designers, researchers, and fellow engineers.

• Cutting-Edge Tools & Technology: Access to state-of-the-art hardware, software development tools, VR/AR equipment, and robust computing infrastructure essential for AI and XR development.

• Team Interaction: Ample opportunities to interact with the immediate XR/AI engineering and UX teams, as well as broader Google product and research groups, fostering knowledge sharing and cross-pollination of ideas.

Work Schedule:

• The role is full-time, typically requiring approximately 40 hours per week.

• While on-site, Google generally offers a degree of flexibility in daily schedules, allowing engineers to manage their time effectively to meet project deadlines and personal needs, provided core collaboration hours are maintained.

📝 Enhancement Note: The on-site work environment in San Jose is designed to maximize collaboration and innovation. It provides the necessary infrastructure and access to talent that is crucial for cutting-edge work in AI and XR, supporting a productive and engaging work experience for operations and engineering professionals.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A recruiter will review your application and resume to assess alignment with minimum qualifications.

• Technical Phone/Video Screen: Expect a technical interview with an engineer or hiring manager to discuss your front-end, server-side, and XR development experience, as well as your understanding of data collection principles.

• On-site/Virtual Loop: A series of interviews (typically 4-5) covering various aspects:

  • Coding/System Design: Technical problem-solving, algorithm design, and system architecture discussions relevant to XR and data collection.
  • UX/Product Focus: Discussions on user experience principles, interface design, and how you approach user-centric development.
  • Behavioral/Situational: Questions assessing your collaboration skills, problem-solving approach, and how you handle challenges, particularly in cross-functional teams.
  • Portfolio Review: A dedicated session to present and discuss your portfolio projects, demonstrating your practical skills and impact.

• Hiring Committee Review: Your interview feedback is reviewed by a committee to ensure fairness and consistency in hiring decisions.

• Team Matching (if applicable): Depending on the specific team needs, there might be a process to match you with the best-fit team.

Portfolio Review Tips:

• Curate for Relevance: Select 3-5 of your strongest projects that directly showcase your skills in front-end development, Node.js, API integration, and ideally, XR development or data collection for AI.

• Highlight Your Role & Impact: For each project, clearly articulate your specific contributions, the challenges you faced, the solutions you implemented, and the measurable outcomes or impact achieved (e.g., improved data accuracy, enhanced user workflow, faster processing).

• Showcase Process & Problem-Solving: Be prepared to walk through your design and development process. Explain your decision-making rationale, how you collaborated with others, and how you overcame technical hurdles.

• Prepare for Technical Deep Dives: Anticipate questions about the architecture, technologies used, and specific coding challenges within your portfolio projects.

• Demonstrate XR/Data Focus: If you have XR or AI data collection projects, emphasize the unique challenges and solutions related to these domains, such as handling spatial data, real-time processing, or ensuring data integrity for machine learning.

Challenge Preparation:

• Coding Challenges: Practice common coding interview problems focusing on data structures, algorithms, and JavaScript. LeetCode (Easy/Medium) is a good resource.

• System Design: Prepare for system design questions related to building scalable applications, managing data pipelines, or designing APIs. Consider how you would architect an XR data collection system.

• UX/Product Sense: Think about how you would approach designing user interfaces for XR devices or improving data collection workflows from a user perspective.

• Behavioral Questions: Prepare answers using the STAR method (Situation, Task, Action, Result) for common behavioral questions related to teamwork, problem-solving, and handling ambiguity.

📝 Enhancement Note: The interview process at Google is rigorous and aims to assess a wide range of skills. For this role, expect a strong emphasis on both core engineering competencies and specialized knowledge in XR and data handling. A well-prepared, relevant portfolio is crucial for demonstrating practical application of these skills.

🛠 Tools & Technology Stack

Primary Tools:

• Front-End: JavaScript (ES6+), HTML5, CSS3, potentially frameworks like Vue.js, React, or Angular for UI development.

• Server-Side: Node.js for backend services, API development, and potentially real-time communication.

• APIs & Protocols: RESTful APIs, gRPC for efficient inter-service communication, and potentially GraphQL.

• Version Control: Git, GitHub/GitLab/Bitbucket for code management and collaboration.

Analytics & Reporting:

• Data Visualization: Tools like Tableau, Looker (Google's own BI platform), or D3.js for creating dashboards and visualizing data related to user interactions and data collection performance.

• Analytics Platforms: Google Analytics, or custom internal analytics tools for tracking user behavior and application performance metrics.

• Performance Monitoring: Tools for monitoring application performance, API response times, and hardware data flow.

CRM & Automation:

• CRM: While not explicitly mentioned for this role, understanding CRM concepts (e.g., Salesforce, HubSpot) can be beneficial for understanding sales/customer data pipelines if applicable.

• Cloud Platforms: Familiarity with cloud services like Google Cloud Platform (GCP) – particularly services like Compute Engine, Cloud Functions, Cloud Storage, and potentially Spanner or BigQuery for data handling.

• XR Development Platforms: Unity, Unreal Engine, ARCore, WebXR frameworks for building XR experiences.

• Database Management: Experience with relational databases (SQLite, PostgreSQL, Spanner) and potentially NoSQL databases for storing and managing collected data.

📝 Enhancement Note: Proficiency across a broad spectrum of development tools, from front-end and back-end technologies to XR platforms and cloud services, is essential. The ability to integrate these tools and manage data effectively within the Google ecosystem is a key requirement for success in this role.

👥 Team Culture & Values

Operations Values:

• User Focus: A deep commitment to understanding and serving the needs of users, ensuring that all data collection and interface development efforts enhance the user experience.

• Innovation & Experimentation: Encouragement to explore new ideas, experiment with cutting-edge technologies (AI, XR), and push the boundaries of what's possible in user interaction and data generation.

• Data-Driven Culture: Reliance on data and empirical evidence to guide decisions, measure impact, and drive continuous improvement in processes and products.

• Collaboration & Inclusivity: Fostering an environment where diverse perspectives are valued, and cross-functional teams work together effectively towards common goals.

• Efficiency & Scalability: Designing and implementing solutions that are not only functional but also efficient, scalable, and maintainable to support Google's global operations.

Collaboration Style:

• Cross-Functional Integration: Expect to work closely with UX Designers, Researchers, Product Managers, AI/ML Engineers, and Hardware Engineers. Collaboration is key to bridging the gap between design intent, technical feasibility, and operational execution.

• Open Feedback Loops: A culture that values constructive feedback, encouraging open communication and iterative refinement of designs, code, and processes.

• Knowledge Sharing: Emphasis on sharing learnings, best practices, and technical insights across teams through documentation, presentations, and internal forums.

• Agile Methodologies: Adoption of agile principles means embracing iterative development, continuous integration, and flexible adaptation to project requirements and user feedback.

📝 Enhancement Note: The team culture at Google emphasizes a blend of technical excellence, user advocacy, and collaborative innovation. For an operations-focused role within XR/AI, understanding and embodying these values will be crucial for effective integration and contribution.

⚡ Challenges & Growth Opportunities

Challenges:

• Rapidly Evolving Technologies: Staying current with the fast-paced advancements in AI, XR hardware, and software development techniques requires continuous learning and adaptation.

• Hardware-Software Integration Complexity: Bridging the gap between diverse hardware APIs and software applications can present complex integration challenges, demanding robust problem-solving skills.

• Data Quality and Management: Ensuring the accuracy, integrity, and efficient management of collected data for AI model training and XR experiences is a continuous operational challenge.

• Cross-Functional Alignment: Effectively aligning technical capabilities with design visions and product requirements across multiple specialized teams can be demanding.

• Scaling Solutions: Developing solutions that are not only functional for prototypes but also scalable to support widespread product deployment and large-scale data processing.

Learning & Development Opportunities:

• Specialized XR/AI Training: Access to internal and external training programs focused on advanced XR development, machine learning, computer vision, and data science.

• Industry Conferences & Workshops: Opportunities to attend leading tech conferences (e.g., GDC, SIGGRAPH, NeurIPS) to stay abreast of industry trends and network with peers.

• Mentorship Programs: Participation in mentorship programs to gain guidance from experienced engineers and leaders within Google, fostering career growth and skill development.

• Internal Mobility: The vastness of Google allows for opportunities to move between different teams and projects, enabling exploration of various domains within AI, XR, and software engineering.

• Access to Cutting-Edge Research: Exposure to Google's extensive research in AI and XR, providing insights into future technological directions and potential career specializations.

📝 Enhancement Note: This role presents significant challenges due to the frontier nature of AI and XR, but these challenges are directly linked to substantial growth opportunities. Continuous learning and adaptation will be key to navigating this dynamic field and advancing one's career.

💡 Interview Preparation

Strategy Questions:

• Foundational AI/XR Data Strategy: "If you were tasked with building a system to collect diverse user interaction data for training an AI model in an XR environment, what would be your initial steps, key considerations for data integrity, and primary technical challenges you anticipate?"

  • Preparation Advice: Focus on outlining a structured approach: defining data types, selecting appropriate sensors/APIs, implementing data validation/cleaning processes, and considering privacy implications. Highlight your understanding of the operational pipeline for AI data.

• Cross-Functional Collaboration in XR: "Describe a situation where you had to collaborate with UX designers and hardware engineers on an XR project. How did you ensure effective communication and alignment between design intent, hardware capabilities, and software implementation?"

  • Preparation Advice: Use the STAR method to provide a concrete example. Emphasize your ability to translate technical constraints to designers and user needs to hardware teams, showcasing your role as a bridge-builder.

• Problem-Solving with Hardware APIs: "Imagine a scenario where a new experimental hardware API is returning inconsistent data. How would you approach diagnosing and resolving this issue, and what steps would you take to ensure reliable data collection for your application?"

  • Preparation Advice: Detail your debugging methodology, including systematic testing, logging, isolating variables, and communicating with the hardware team. Showcase your analytical and problem-solving skills.

Company & Culture Questions:

• User-Centric Development at Google: "How does Google's 'Focus on the user' philosophy influence your approach to building software, especially in the context of XR and AI data collection?"

  • Preparation Advice: Connect your personal work philosophy to Google's stated values. Discuss how you prioritize user needs, even when dealing with complex technical or data-centric tasks.

• Teamwork in a Fast-Paced Environment: "Google's environment is fast-paced and involves working with many teams. How do you manage your workload, prioritize tasks, and contribute positively to team dynamics?"

  • Preparation Advice: Highlight your organizational skills, time management techniques, and experience working collaboratively in agile or project-based teams.

Portfolio Presentation Strategy:

• Narrative Structure: Frame your portfolio projects with a clear beginning (problem/goal), middle (your solution/process), and end (results/impact). Tell a story that highlights your contributions.

• Quantify Impact: Whenever possible, use metrics to demonstrate the success of your projects. For example, "Reduced data processing errors by 20%" or "Improved user task completion time by 15%."

• Technical Depth & Clarity: Be prepared to explain the technical architecture, key libraries, and design choices clearly and concisely. Avoid jargon where simpler terms suffice, but be ready for deep technical dives.

• Showcase XR/Data Relevance: Explicitly connect your portfolio projects to the requirements of this role – how your front-end skills, Node.js experience, or XR work demonstrate your capability in data collection and building immersive experiences.

📝 Enhancement Note: Interview preparation should focus on demonstrating not just technical proficiency but also a strong understanding of user experience, collaborative capabilities, and the operational aspects of building AI/XR products. A well-prepared portfolio is your primary tool for showcasing these skills.

📌 Application Steps

To apply for this operations-focused UX Engineering position:

• Submit your application through the official Google Careers portal via the provided link.

• Portfolio Customization: Tailor your resume and portfolio to highlight specific experience with JavaScript, HTML5, CSS, Node.js, API integration, and any XR/AR/VR development or data collection projects. Select your most relevant projects for a focused presentation.

• Resume Optimization: Ensure your resume clearly articulates your years of experience, specific technical proficiencies, and quantifiable achievements in front-end and server-side development, with a strong emphasis on any experience related to hardware, data collection, or XR.

• Interview Preparation: Practice coding problems, system design scenarios, and behavioral questions, focusing on examples that demonstrate your problem-solving skills, collaboration abilities, and user-centric approach, particularly within the context of AI and XR. Prepare a concise and impactful presentation of your portfolio.

• Company Research: Familiarize yourself with Google's mission, its work in AI and XR, and its core values. Understand how your role contributes to the company's broader objectives in these innovative fields.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.