General Questions

Be Positive and Enthusiastic: Dont Oversell yourself
Use Metrics to Describe Impact: Use values like "improved by 30%"
Show Collaboration: Highlight teamwork in the same team and cross-functional interactions.
Tailor Answers to the Role: Emphasize skills most relevant to the position

0. Tell me about yourself.

Keep it under one minute and adjust the details to fit your experience and the specific role.

Professional Titles:
- Rendering and Pipeline Technical Artist
- Product Design and Software Engineer Prototyper
Years of Experience in specific industry:
- 10 Years in Tech and Entertainment
What I work on:
- Started career working in Anim/VFX/Games Pipeline
- Synthetic Data Pipelines for AI
- Prototyping Minimal Viable Products for XR
Current Goal and Connection to Position:
- I'm looking to work at the intersection of Creativity and Engineering
- (Customize line to how the JD connects with my goal)
What I'm doing since unemployed:
1. Traveling to create Immersive Content like Gaussian Splats and 360 photography
2. Building a Creature Collection App to submit to conferences,

I’m a Technical Artist and Software Engineer Prototyper in the Tech and Entertainment industry for the past ten years, starting in traditional animation/vfx/games pipeline before transitioning to synthetic data pipelines for AI and prototyping minimal viable products for XR. I work best at the intersection of creativity and engineering (Custom to Company or Job Description). For fun, I've been focused on Travel to create Immersive Content Creation using 360 cameras, Photogrammetry, and Gaussian Splats. I'm also building a mobile AR Pokemon Go + photography app to submit to conferences.

1. Tell me why you will be a good fit for the position.

Why do you want to work for X?

What are you looking for next role?

Collaboraing with a multidisiciplnary team on challenging work to launch an impactful product
Increasing Scope beyond individual contributor to work with crossfunctional partners and customers to aid product roadmap

I’m looking for a role where I can work on challenging pipelines and collaborate with a multidisciplinary team to launch an impactful product.

I’m excited about company’s work in [specific area], and I’m eager to bring my technical expertise and passion to the team. I’m impressed by X company’s innovative work in [specific area]. I admire your commitment to [a value or mission, e.g., open-source contributions or sustainability].

As someone who [your relevant strength,], I’m excited about the opportunity.

2. What happen to your last company?

Acknowledge the situation without overexplaining
- BG Checks from future employers do not show PIPs, only time of employment with previous company. This means you do not need to admit to poor performance.
Stay Positive and Highlight your Value: Shift Focust to achievements and skills you developed, and agerness to contribute to the new role and be confident.

I was part of a company-wide re-org that ended my contract short. However, my last role at Meta, it provided me with experience in increasing my scope beyond an Individual Contributor, as I worked with Directors and VPs across multiple departments on unifying multiple AR and AI product roadmaps into a cohesive strategy.

Present accessibility focused prototypes to internal leadership and execs from external companies.

Worked on unifying their Internal prototyping pipeline for various AR/AI hardware prototypes.

Organize internal AR Demo Summit to connect hundreds of people across the globe to present their work.

3. What project are you currently working on?

Augmented Reality: Unity AR Game with Generative AI imageTo3D and Gaussian Splats
Human Centric AI: Realtime digital humans, like open source LLM, shaders, and rigging.

I'm working on upskilling my knowledge in AR and human centric AI

From 2017-2019, I was the lead AR engineer for the official Siggraph conference ScavengeAR App, an app designed for attendees photograph 3D creatures spawned from 2D Artwork hidden throughout the conference. We had over 1000 Daily Active Users throughout the conference. The Pandemic killed the app, but with the return of inperson conferences, I've refactored the app to utilize the latest tech stack.

My other speciality is real time digital humans. I have a background in Theater and Filmmaking, so I'm fascinated about solving the uncanny valley. The first part of my career i focused alot on visuals, but with the emergence of LLM and synthetic voice, I realize that its about solving all the components.

4. How do you stay up to date with latest tech

Converting "doom-scroll" to "micro-learning" by joining tech communities on Linkedin and Reddit
- Read latest papers from such communities
Go to conferences to network and try latest hardware

I stay up to date with latest tech by making information come to me by

Joining communities on Reddit and Linkedin, which customizes my social media feed to content I like.

Those posts lead to links to latest papers, which I can try the latest repos on Hugging face or Github.

I also volunteer for conferences such as GDC, SIGGRAPH, and Visual Effects Society, where I can go and try the latest hardware.

5. Where Do You See Yourself in Five Years?

Launching Product Roadmap [features] to customers on an impactful team
Growing as an expert Individual Contributer, and making important decisions that impact the product

In five years, I see myself growing both technically, creatively, and professionally in a role that challenges me and allows me to make a meaningful impact on a successful product.

I aim to deepen my expertise in [specific area]

Continuing to work crossfunctionally to better aid the product roadmap at a larger scope, whether that is working more closely to customers and stakeholders, or leading a team to create the next feature for the product

STAR

Communication Questions

6. What frustrates you?

Lack of communications among teams leading to longer delivery time and a poorer product.

Situation:
At Samsung Research, I was the first tech artist to bridge the gap between the design team and engineering team for for a video centric real-time digital human concierge product.

Task:
It took two weeks for artists to do production and post production before they can deliver to the machine learning team. Not scaleable in the long run. They want to speed up our delivery.

Action:
I setup individual meetings with artists and engineers to understand their workflow in order to narrow down our requirements. I ran the current process from end-to-end myself, and identified inefficiencies.

Artists are use to deliverying data for creative studios, which include video at the highest quality raw, 12k resolution, and multiple layers. This takes a lot of time to shoot and process. I identified in code that machine learning team ultimately down rez, changed the codec, and flatten the data in code.

Artists and Engineering are never sure if its the data's fault or the machine learning model. I built their preprocessing pipeline which generate video diagnostics and upload to our documentation per delivery.

After improving the post production pipeline, I converted our production pipeline to better suit R&D. The bigger picture is to speed up delivery, so I had to teach myself production pipeline. I added multicam, mocap, increased network capacity.

Result:
Sped up data delivery from 2 weeks to 1 day.

7. How do you handle multiple stakeholders and priorities?

Talk to each stakeholder individually and work with manager, who has larger scope, on a priority matrix and resource allocation
Turn each priority to a Kanbam board to Requested, Doing, and Done.
Even if it's just acknowledgement, make sure the stakeholder doesn't feel ignored, even if you determine their priority isn't the highest.

Situation:
At Meta I was their first Product Design Prototyper on the Design Program Management Team in at AI/AR Wearables Division. I worked with Engineers, Artists, Product/Project Managers across multiple groups. They hired me because of

Prototyper and Tech Art experience at Samsung R&D building Minimal Viable Products

Systems Engineering experience at PlayStation under the Marketing Communcations group.

Program Management and AR Engineer for SIGGRAPH conference.

Task:

Improve the internal demo delivery of our hardware software prototyping pipeline across all teams and

Aid on product roadmap by giving presentations to VPs and our Partner Execs.

My first major milestone is to successfully throw an AR Demo Summit for employees to try the latest tech. This will help me understand the org and get introduced to prototypers in other teams.

Action:

Work with manager, who has a higher scope, on my priorty matrix from P0 to P4 on what demos should present to what audience.

Instead I created a kanbam board that keeps track of Requested, Doing and Done Tasks.

Make good documentation for when we do this again, or when AI crawls for their LLM.

When talking to people

Be positive and acknowledge responses

Build genuine connections. I will need their feedback later for prototyping pipeline

Categorize specific communication thread as Single Source of Truth.

Result :
Successfully threw an AR Demo Summit which spanned across Menlo Park, Redmond, New York, and London with hundreds of attendees. Built connections to understand why our current prototyping pipeline has been deprecated and understand how the org works as a whole, but contract was cut short before major progress can start.

8. Describe a situation where you had to explain a complex idea to a non-technical person.

Know Your Audience: Understand their level of familiarity based on their role
Start with the Big Picture: Begin with the "why" and explain the purpose of the topic before diving into details
Use analogies: Relate the concept to something they already understand
Break it down to chunks:
- When explaining how an API works:
  1. "Imagine you're at a restaurant.
  2. The menu is like the API—it lists what you can request.
  3. You place an order with the server (the API), and it brings back your food (the response)."
Use Visual Aids
Avoid overly technical jargon: Instead of "distributed systems," say, "a setup where multiple computers work together to handle large tasks."
Check for Understanding and Be Patient: Don't rush and ask "Would you like me to explain another way?"

Cloud computing is like renting storage and tools in a warehouse instead of owning them. Instead of buying expensive hardware, you can use someone else’s equipment and only pay for what you need, like storing photos or running applications. It’s convenient because you can access it from anywhere with the internet.

9. Tell me about a time you had a disagreement with your manager.

Focus on how you resolved the disagreement professionally and what you learned.
Avoid blaming your manager or making the disagreement seem adversarial.

Situation:
When out product was exiting R&D and going into Production, manager and I disagreed on how much resources we should put into our Digital Asset Management system.

Task:
Having worked at Sony when they were hacked, I care a lot about keeping data secure.

Action:
I was given a budget to implement our DAM system. I decided to go for an Open Source solution and hiring a technically minded Digital Asset Manager

Result:
We launched the DAM and product went into Production.

10. Give an example of a time you received critical feedback. How did you respond?

Early in my career, my manager pointed out that I have trouble retaining information in the mornings, but not the afternoons, which lead to me asking redundant questions in the morning at times. They encouraged me to take the same focus i exhibit in the afternoon to mornings. On a more personal note, i didnt know at the time i was suffering from Sleep Apnea, so every morning i woke up with headaches. I solved this buy carrying a notebook around to jot everything down. A physical notebook, as intitally i used my cellphone to take notes but people felt like i wasnt listening when taking notes on cellphone. I then put it in the notes in the secure internal wiki. I also took my health more seriously and went to a few doctors appt which lead to my diagnosis. Now, not only do i take notes at work, it just became a habit to take notes in life. I maintain my own personal wiki that i maintain for skil building like cooking and working out, and i also use Flashcards at night to help me maintain my knowledge via a question answer format.

11. Tell me about a time when you had a conflict with a co-worker.

Use the STAR method: Situation, Task, Action, Result
Focus on Resolution: Highlight how you approached the conflict constructively.
Focus on listening and understanding: Show how you addressed concerns and presented solutions.
Demonstrate leadership: Explain how you persuaded the person without forcing a decision.

Pipeline Example:

Situation:
In one project, a teammate and I disagreed on the best approach for implementing a feature. He preferred a quick fix, while I believed a scalable solution was better long-term.

Task:
We needed to agree on an implementation to meet the deadline.

Action:
I initiated a conversation to understand his concerns and shared my perspective with data showing the benefits of scalability. We collaborated to find a middle ground by implementing a solution that was scalable but prioritized immediate needs.

Result:
This not only resolved the conflict but also improved our collaboration and led to a successful project delivery.

Product Example:

Situation:
During a sprint, I proposed refactoring part of the codebase to improve maintainability, but a senior developer opposed it, citing time constraints.

Task:
I needed to convince the team that the refactor was critical without jeopardizing timelines.

Action:
I gathered data showing the technical debt risks and prepared a proposal to divide the refactor into smaller tasks over multiple sprints. I also ensured the changes wouldn’t delay immediate deliverables.

Result:
The team agreed with the plan, and we successfully reduced technical debt while staying on track with deadlines.

12. How Do You Use AI to Increase Productivity in Your Work?

I use GitHub Copilot and ChatGPT to learn new topics and write boilerplate code, while keeping in mind data security
Use role prompting for AI to give design feedback, like show it an animated GIF or using image2image genai for UI.
Recognize halluncinations and that AI can take you down the wrong path if not familiar with architectural thinking and good practices. AI does not know the latest APIs depending on when data is scraped, so need to refactor accordingly.

I use ChatGPT to streamline coding by suggesting boilerplate code or offering solutions for repetitive tasks. This allows me to focus more on solving complex problems and refining the architecture of my applications. I also leverage input like animated GIFs and images for feedback and generating new UI based on design terminology.

13. Have you ever worked on a cross-functional team? What role did you play.

Focus: Team collaboration and bridging disciplines.

Talk about leading a small team at Samsung composted of engineer and designers

Talk about Meta experience workign with Directors and VP

Software Engineering Questions

14. Tell me about a time you solved a difficult technical problem

Focus on a technical or team-related challenge you’re tackling.
Explain how you're addressing it and what you’re learning in the process.

Technical Artist

The most challenging aspect of my current project is ensuring high availability while transitioning to a new cloud provider. We need to maintain uptime during the migration, which requires careful planning and thorough testing of failover strategies. I've been collaborating closely with the team to simulate different failure scenarios and refine our approach.

Software Engineer

The most challenging aspect of my current project is ensuring high availability while transitioning to a new cloud provider. We need to maintain uptime during the migration, which requires careful planning and thorough testing of failover strategies. I've been collaborating closely with the team to simulate different failure scenarios and refine our approach.

15. What was the most difficult bug that you fix?

Choose a bug that highlights your technical and debugging skills.
Focus on the process and tools you used to solve it.

Technical Artist

I recently fixed a memory leak in a microservice that caused intermittent crashes during peak traffic. Identifying the leak was challenging because it only occurred under specific load conditions. Using tools like Valgrind and custom logging, I traced the issue to a third-party library that wasn’t releasing resources properly. I updated the library and wrote additional tests to ensure it didn’t recur. It was a great reminder of the importance of monitoring and profiling in production systems.

Software Engineer

I recently fixed a memory leak in a microservice that caused intermittent crashes during peak traffic. Identifying the leak was challenging because it only occurred under specific load conditions. Using tools like Valgrind and custom logging, I traced the issue to a third-party library that wasn’t releasing resources properly. I updated the library and wrote additional tests to ensure it didn’t recur. It was a great reminder of the importance of monitoring and profiling in production systems.

16. How did you improve the workflow of a team?

Have you ever had to advocate for using a framework?

Choose an example where advocating for something resulted in positive change.
Show persistence and the ability to influence others.

Centralized storage for digital assets like images, videos, audio, and datasets.
Metadata tagging, categorization, and version control for easy search and retrieval.

ML models require large, well-organized datasets for training and inference. ResourceSpace ensures assets are:
Organized: Proper tagging and metadata allow for quick filtering by specific attributes (e.g., image resolution, format, or labels).
Easily Accessible: Centralized data prevents duplication and streamlines data access.

Metadata can serve as labels or features for supervised learning models.
Example: Images tagged with “dog” or “cat” can be directly used for classification tasks.
Streamlines the labeling process, reducing the time required for manual data preparation.
3. Version Control and Asset History

Tracks versions of assets, ensuring changes are logged and reversible.
Allows you to compare different versions of assets.
Why It’s Useful for ML Pipelines:

Training datasets evolve over time, and having version control ensures:
Consistency: ML models can be retrained on the same dataset versions.
Traceability: You can roll back to previous versions if a new dataset causes unexpected model behavior.
4. Integration with ML Pipelines
What ResourceSpace Provides:Bulk export tools for transferring large datasets to ML pipeline systems.

Programmatic access via APIs allows:
Automation: Automate data extraction and preprocessing for your pipeline.
Scalability: Easily handle large datasets and integrate with cloud-based pipelines (e.g., AWS SageMaker, TensorFlow, or PyTorch).
Bulk exports simplify transferring datasets to training environments.
5. Security and Permissions
Encryption and secure file transfers.
Why It’s Useful for ML Pipelines:

Ensures data security and compliance, especially when handling sensitive datasets (e.g., medical images, financial records).
Role-based permissions allow only authorized personnel or systems to access and modify datasets, reducing errors and ensuring auditability.
6. Streamlined Preprocessing

Support for custom workflows and batch operations (e.g., resizing images, converting file formats).
Plugins for extended functionality.

Preprocessing (e.g., resizing images or normalizing data) is often required before feeding data into ML models. ResourceSpace can handle:
Batch preprocessing: Prepares assets for direct use in ML workflows.
Data normalization: Ensures assets meet the pipeline’s input requirements.
7. Collaboration and Audit Trails

Collaboration features for teams to manage and annotate datasets.
Detailed logs of who accessed or modified assets.
Why It’s Useful for ML Pipelines:

Efficient Dataset Management: Multiple team members can contribute to cleaning, labeling, or organizing the dataset.
Accountability: Audit trails help track changes and identify potential data issues that may impact model performance.
Here’s how ResourceSpace DAM can integrate into an ML production pipeline:

Data Ingestion:

Upload raw assets (e.g., images, videos) into ResourceSpace.
Use metadata fields to tag assets with relevant information (e.g., labels, source, resolution).
Data Selection:

Query the ResourceSpace database for specific subsets of data (e.g., “images tagged as ‘cat’ with resolution > 1080p”).
Use API calls to retrieve assets programmatically.
Preprocessing:

Perform bulk operations like resizing, cropping, or format conversion within ResourceSpace.
Export preprocessed data to the ML pipeline environment.
Pipeline Integration:

Use ResourceSpace APIs to feed data directly into ML pipelines.
Automate periodic updates to the dataset by syncing ResourceSpace with cloud storage or ML frameworks.
Model Training and Evaluation:

Use the exported dataset to train ML models.
Feedback Loop:

In one project, I had to push for a Digital Asset Management system for our Final Preprocessing before data is passed off to Machine Learning. Our old way was publishing our data to a file system, but it lead to alot of issue where the data was still being touched by other teams. This lead to shortcuts where researchers at time would modify the data after QC, which lead to occasional bad ML results. Bad results were fine for R&D but not acceptable for a product and the data preprocessing team was held responsible at times. By implementing a DAM, the data was pulled through an API, was more secure because training data cannot be accessed via filesystem, and also had an interface where they could view diagnostic information and search through data via metadata. For instance, like looking at all our idle poses at once. This made the data safer and more exploratory. The best thing about this DAM? We used an opensource platform that cost us negligble about of money to implement.

17. Tell me about a project where you faced unexpected challenges. How did you handle them?

Focus: Adaptability, resilience, and creativity.

Building Motion capture lab asap

Problem, we thought 2d data was enough but realized we need 3d data. 3d data from mediapipe is poor
Start with rented equipment. I used my connections at Magic Leap to find the best price for data. Solves short term problem
Getting Vendor option from Real Mocap
Narrow down machine learning requirements
1. Art team didnt ask question about delivery other than deliver best quality data
  1. includes so many render passes we dont need
2. Research group take data and transcode them to smaller data for ML
Experiment with AI, off the shelf and repos
Build System and make sure the limits of the

Situation:
Task:
Action:
Result:

18. Tell me about a time you met a tight deadline.

Tell me about a time you had to prioritize tasks in a large project.

Focus: Time management and decision-making.

Use the STAR method (Situation, Task, Action, Result) to structure your response.
Emphasize planning, teamwork, and focus under pressure. Trust

Deadline for Leapcon and Royalshakeaspeare.

Sitiuation:
Our team was tasked with delivering a critical feature for a client demo in just two weeks.

Task:
I needed to ensure the feature was fully functional and aligned with the client’s requirements within the deadline.

Action:
I worked with the team to define the MVP, prioritized key tasks, and streamlined communication to avoid delays. We worked extra hours when necessary and conducted daily stand-ups to track progress.

Result:
We delivered the feature on time, and the demo was a success. It reinforced the importance of prioritization and maintaining focus under pressure.

19. Describe a time when you had to refactor legacy code. How did you approach it?

Here's a structured way to answer this question, tailored to your experience with refactoring your AR project:

---

### **1. Briefly Set the Context**
Start by describing the legacy code and the purpose of the project, focusing on the challenges or limitations of the existing system.

Example:
*"In 2024, I refactored a 5-year-old AR project originally built with Vuforia and Unity for augmented reality experiences. The project was outdated and relied on legacy libraries, which no longer aligned with modern AR frameworks like AR Foundation. Additionally, the codebase lacked modularity, and maintaining or expanding features had become cumbersome."*

---

### **2. Explain the Problem**
Highlight the key issues with the legacy code and why refactoring was necessary.

Example:
*"The legacy code used Vuforia 9, which had limitations in compatibility with newer Unity versions and modern AR SDKs. Furthermore, features like image tracking and ground planes were tightly coupled, making it difficult to switch to AR Foundation. Performance was also a concern due to inefficiencies in the original code, such as redundant object hierarchies and overuse of runtime-generated assets."*

---

### **3. Describe Your Approach**
Outline the steps you took to refactor the code, focusing on your planning, execution, and any tools or strategies used.

Example:
*"I began by analyzing the legacy project to identify reusable components, such as 3D models and animations, and separated them from code that required updating. Next, I mapped out the feature set provided by Vuforia and determined equivalents in AR Foundation. I set up a new Unity project with AR Foundation 5.1, progressively integrating updated features like tracked image management and ground plane detection. To ensure scalability and maintainability, I restructured the codebase to use modular design patterns, such as decoupling AR tracking logic from scene-specific behaviors. This also allowed me to implement sprite animations and improve performance with optimized lighting settings for AR environments."*

---

### **4. Highlight the Results**
Show the impact of your refactoring work and how it improved the project.

Example:
*"The refactored project became significantly more maintainable and scalable. By transitioning to AR Foundation, I ensured compatibility with both iOS and Android devices using a single framework. The modular design allowed for easier integration of new features, such as XR simulation, and reduced build times by optimizing texture handling. The updated app achieved better performance and provided a smoother user experience, while also aligning with current AR standards."*

---

### **5. Reflect on What You Learned**
Conclude by sharing what you gained from the experience and how it enhanced your skills.

Example:
*"This experience taught me the importance of understanding both the legacy framework and the target framework before beginning a refactor. I also improved my skills in modular design and cross-platform AR development, which have been invaluable for future projects."*

---

### Complete Example Response:
*"In 2024, I refactored a 5-year-old AR project originally built with Vuforia and Unity. The codebase was outdated, tightly coupled, and no longer compatible with modern AR standards. I started by analyzing reusable components and mapping legacy features to AR Foundation equivalents. I set up a new Unity project with AR Foundation 5.1 and progressively integrated features like tracked image management and ground planes, while restructuring the codebase for modularity and maintainability. The result was a more performant, scalable, and maintainable application compatible with modern AR platforms. This experience enhanced my skills in modular design and cross-platform AR development, and taught me the importance of planning before undertaking a large-scale refactor."*

This approach highlights your technical skills, problem-solving ability, and project impact in a structured way. Let me know if you'd like to refine it further!

20. Describe a project where you improved the performance of a system.

- Focus: Optimization, technical skills, and impact.

scavengeAR?

21. Describe a project where you improved the scalability of a system.

Renderfarm

22. Can you give an example of a time you made a mistake in your code? How did you fix it?

ScavengeAR. made everythign in HLSL.

Creating an entire Unity UI in HLSL (High-Level Shader Language) instead of using Unity's Canvas system can be problematic due to several technical and practical reasons. While HLSL is powerful for creating custom visual effects, using it exclusively for a UI introduces significant challenges that make it less suitable compared to Unity's Canvas-based system. Here's why:

1. Complexity of UI Layout and Interaction
Canvas:

Unity's Canvas system provides built-in tools for layout management, such as anchors, pivots, and RectTransforms.
Easily handles dynamic resizing, positioning, and responsiveness across various screen sizes and resolutions.
Includes event systems for detecting clicks, drags, and other user interactions (e.g., buttons, sliders).
HLSL:

HLSL is primarily designed for rendering and lacks the concept of layout or user interaction.
To recreate layout management in HLSL, you would need to manually calculate positions, handle transformations, and account for screen resolution changes, which is extremely time-consuming.
Implementing interactive elements like buttons or sliders would require additional logic in scripts, effectively recreating Unity’s existing UI framework from scratch.
2. Lack of Accessibility Features
Canvas:

Unity's UI system supports accessibility features such as screen readers and keyboard navigation.
You can easily add animations, transitions, and tooltips to UI elements.
HLSL:

You would need to manually program accessibility features, which is not only challenging but also prone to errors.
Building animations and transitions would require custom shader logic, making maintenance and iteration harder.
3. Performance Considerations
Canvas:

Unity's Canvas system is optimized for UI rendering. The engine batches and manages draw calls efficiently for most common UI use cases.
Unity provides tools like Canvas Scalers to adjust the UI for different screen sizes without extra performance overhead.
HLSL:

Writing the entire UI in HLSL would require a full-screen quad (or multiple quads) to render elements, which means every pixel might be processed unnecessarily.
Without careful optimization, this approach can result in excessive GPU usage, especially if shaders include complex calculations for every frame.
4. Lack of Unity Editor Integration
Canvas:

The Canvas system integrates seamlessly with the Unity Editor, allowing you to design UI visually with tools like the RectTransform Editor and Prefabs.
Designers and artists can contribute without needing to write code or shaders.
HLSL:

Designing a UI in HLSL would require writing code for every single visual element and interaction.
This lack of a visual editor makes the workflow slower and limits collaboration with non-programmers.
5. Debugging and Maintenance
Canvas:

The Canvas-based UI leverages Unity's debugging tools, including the Scene view and UI event system.
Issues like misaligned elements or broken interactions are easy to identify and fix.
HLSL:

Debugging shader-based UI involves interpreting pixel-level behavior, which is far less intuitive.
Small changes to the design could require significant rework of shader code.
6. Scalability
Canvas:

Unity's UI system scales well for typical 2D and 3D applications, supporting features like nested canvases, localization, and animations.
It’s easy to add or remove UI elements without disrupting the entire layout.
HLSL:

Adding new UI elements in HLSL requires modifying shader code, which can make the system fragile and error-prone.
Scaling the UI to different screen sizes or adding responsive layouts becomes a major challenge.
When to Use HLSL for UI
HLSL can still be a good choice for specific visual effects in the UI, such as:

Creating custom shaders for buttons, text, or backgrounds (e.g., animated gradients, outlines, or glows).
Implementing unique effects like holographic or glitch effects for menus.
Enhancing Canvas-based UI with shaders rather than replacing it entirely.
In these cases, HLSL complements the Unity Canvas rather than replacing it, allowing you to benefit from the strengths of both.

Conclusion
Using HLSL to create the entire Unity UI is not recommended because:

It lacks the layout, interaction, and accessibility features of Unity's Canvas system.
It introduces unnecessary complexity and performance overhead.
Maintenance and iteration become significantly harder.
Instead, leverage Unity's Canvas system for the core UI structure and use HLSL sparingly to add custom visual effects. This approach balances usability, performance, and flexibility, ensuring a more robust and maintainable solution.

- Focus: Accountability, troubleshooting, and learning from mistakes.

Technical Art Questions

23. Tell me about a time you optimized a 3D asset pipeline.

- Focus: Problem-solving, efficiency improvements, and technical skills.

24. Have you ever worked on a project where the artistic vision conflicted with technical constraints? How did you balance them?

Performance is critical. Art is about hitting the essence, not hitting exactlt the concept art.

Focus: Negotiation, technical expertise, and artistic understanding.

25. Tell me about a time you implemented a tool or workflow that improved efficiency for your team.

Start with experience building multiple tools (like pyqt tools, photogrammetry, etc), but talk avbout the QC preprocess pipeline

Focus: Tool development and process improvements.

build Preprocessing for samsung

26. Give an example of a time you had to troubleshoot a rendering or asset issue in production.

Focus: Debugging and technical understanding. Learning from multiple occurances.

3D? Deadline logs, understand trends in graphs

2D? QCtools and preview diagnostics