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AI Researcher (CUDA)

AryaXAI stands at the forefront of AI innovation, revolutionizing AI for mission-critical businesses by building explainable, safe, and aligned systems that scale responsibly. Our mission is to create AI tools that empower researchers, engineers, and organizations to unlock AI's full potential while maintaining transparency and safety.

Our team thrives on a shared passion for cutting-edge innovation, collaboration, and a relentless drive for excellence. At AryaXAI, everyone contributes hands-on to our mission in a flat organizational structure that values curiosity, initiative, and exceptional performance.

Requirements:

  • Core Languages: CUDA, Python

  • Frameworks: CUTLASS, pybind11 (or similar)

  • Tools: Nsight, JAX/XLA bindings

  • Focus Areas: GPU Kernel Optimization, Deep Learning Inference & Training

Role Overview

We are looking for a highly skilled AI Researcher - GPU Kernel Developer to join our team and push the boundaries of high-performance AI computation. In this role, you will design, develop, and optimize GPU kernels that power state-of-the-art AI models. Your work will directly influence the performance and scalability of our AI systems.

Key Responsibilities:

  • Develop and refine low-level CUDA kernel optimizations for deep learning inference and training.

  • Profile, debug, and optimize single and multi-GPU operations using tools like Nsight.

  • Deeply understand and exploit GPU memory hierarchies and computational capabilities.

  • Implement cutting-edge methods from research papers into CUDA kernels.

  • Collaborate on designing innovative solutions to achieve peak GPU performance.

Ideal Candidate Profile

We are looking for candidates with a proven track record of excellence in GPU programming and AI system optimization. You should bring:

Core Experiences:

  • Expertise in designing high-performance GeMM CUDA kernels using Tensor cores or CUDA cores, leveraging tools like CuTe or CUTLASS.

  • Proficiency in extending or writing custom attention and deep learning kernels from scratch.

  • Confidence in writing both forward and backward kernels while managing floating-point precision errors.

  • Strong optimization skills for both memory-bound and compute-bound operations.

  • Advanced knowledge of GPU architecture, including register pressure, shared-memory usage, and GPU utilization.

Preferred Skills:

  • Familiarity with profiling tools (e.g., Nsight) to identify bottlenecks and improve performance.

  • Experience integrating custom kernels with frameworks like JAX/XLA through tools like pybind11.

  • Awareness of the latest advancements in GPU optimization techniques for AI workloads.

Why Join AryaXAI?

  • Mission-Driven Impact: Work on challenges that shape the future of responsible AI.

  • Technical Excellence: Collaborate with a team of passionate and experienced professionals.

  • Growth Opportunities: Contribute across domains and expand your expertise in GPU kernel development and AI research.

  • Flexible Work Environment: Choose between remote work or relocation support to one of our key offices.

Interview Process

  • Application Review: We review your CV and a statement of exceptional work.

  • Initial Interview (15 Minutes): A technical team member will evaluate your basic skills and fit for the role.

  • Main Process:

  • Coding Assessment: Solve programming challenges in your preferred language.

  • Systems Problem-Solving: A live, hands-on session to showcase practical expertise.

  • Project Deep-Dive: Present your most notable project to our team.

  • Team Meet & Greet: Engage with the broader AryaXAI team.

Note: Our interviews are designed to conclude within one week to streamline your onboarding process.

What You Should Know About AI Researcher (CUDA), AryaXAI

At AryaXAI, we’re seeking an experienced AI Researcher specializing in CUDA to join our innovative team in Mumbai. We're not just another tech company; we stand at the forefront of AI innovation, creating systems that are not only powerful but also explainable and aligned with mission-critical business needs. As an AI Researcher - GPU Kernel Developer, you will have the unique opportunity to design, develop, and optimize high-performance GPU kernels that drive state-of-the-art AI models. Your work will directly impact the efficiency and scalability of our systems, empowering engineers, researchers, and organizations alike. We pride ourselves on a flat organizational structure where everyone's insights and talents are valued. In this role, you'll work collaboratively with a team driven by a passion for excellence, diving deep into GPU programming, memory hierarchies, and computational capabilities. If you’re ready to tackle challenges that shape the future of responsible AI while enjoying a flexible work environment, let's explore the possibilities together at AryaXAI!

Frequently Asked Questions (FAQs) for AI Researcher (CUDA) Role at AryaXAI
What are the main responsibilities of an AI Researcher at AryaXAI?

As an AI Researcher specializing in CUDA at AryaXAI, your primary responsibilities will include developing and optimizing low-level CUDA kernel optimizations for deep learning inference and training. You'll also profile and debug single and multi-GPU operations and implement cutting-edge methods from research papers into CUDA kernels. Furthermore, collaborating with your team to design innovative solutions to achieve peak GPU performance is a key part of the role.

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What qualifications are needed to become an AI Researcher at AryaXAI?

To excel as an AI Researcher at AryaXAI, candidates should have expertise in CUDA programming, particularly in designing high-performance GeMM kernels and customizing deep learning kernels. Familiarity with profiling tools like Nsight and a strong understanding of GPU architecture are also essential. Proficiency in Python and experience with frameworks such as JAX/XLA are highly desirable.

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What type of projects will an AI Researcher work on at AryaXAI?

As an AI Researcher at AryaXAI, you'll work on projects that involve pushing the boundaries of high-performance AI computation. This includes optimizing GPU kernels, exploring the latest advancements in GPU optimization techniques, and integrating custom kernels. Your contributions will have a direct impact on the performance and scalability of various AI systems.

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How does AryaXAI support employee growth for AI Researchers?

At AryaXAI, we value personal and professional growth. As an AI Researcher, you'll have opportunities to contribute across different domains, collaborate with experienced professionals, and expand your expertise in GPU kernel development and AI research. We ensure a supportive environment that fuels your passion and innovation.

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What is the interview process like for the AI Researcher position at AryaXAI?

The interview process for the AI Researcher position at AryaXAI is designed to be efficient and straightforward. It begins with application reviews followed by a brief initial technical interview. Candidates will then complete a coding assessment, engage in systems problem-solving, present a notable project to the team, and finally meet with the broader AryaXAI team. We aim to complete the process within one week to ensure a smooth onboarding experience.

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Common Interview Questions for AI Researcher (CUDA)
Can you describe your experience with CUDA programming?

In your answer, provide specific examples of CUDA projects you've worked on, mentioning any optimization techniques you've employed. Highlight your familiarity with writing custom kernels or optimizing existing ones, and discuss how you addressed challenges in performance.

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What tools do you use for profiling and optimizing GPU applications?

Mention tools like Nsight or similar that you’ve used for profiling. Describe how you've applied these tools to identify bottlenecks and improve performance, illustrating specific outcomes to showcase your impact.

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How do you go about debugging a CUDA kernel?

Discuss your systematic approach to debugging. Include steps such as using error checks, leveraging debugging tools, and isolating issues in your code. Share an example where your debugging skills resolved a complex issue.

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What strategies do you use for memory optimization in GPU programming?

In your response, highlight the techniques you employ to manage memory efficiently, such as minimizing memory access and understanding memory hierarchies. Discuss how you've implemented these strategies in past projects.

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Can you explain the importance of floating-point precision in GPU kernels?

Explain how floating-point precision affects the accuracy of computations in AI models. Discuss any methods you’ve implemented to manage precision errors effectively, providing examples of your successes.

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How do you keep updated with the latest advancements in GPU optimization techniques?

Talk about your preferred resources for staying informed, such as research papers, journals, or attending conferences. Explain how this knowledge has influenced your work and driven your project innovations.

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Describe a challenging project related to AI computation that you've worked on.

Share a specific project that posed significant challenges. Outline the problem, the techniques you used to address it, and the results achieved. Focus on demonstrating your problem-solving skills and technical expertise.

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What is your approach to working collaboratively with a team on AI research?

Emphasize the importance of communication and teamwork in your collaborative process. Share examples of how you’ve effectively worked with team members to achieve project goals or optimize solutions collectively.

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Have you ever implemented a new technique from academic research into your work? How did it go?

Describe a specific instance where you took an academic technique and adapted it for practical use. Discuss any challenges faced, the implementation process, and the impacts of this technique on your project's success.

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What role do you see AI playing in the future of technology?

Share your perspectives on the evolving impact of AI across industries. Discuss emerging trends and technologies you find exciting, and how you envision contributing to this future in your role at AryaXAI.

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EMPLOYMENT TYPE
Full-time, remote
DATE POSTED
January 13, 2025

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