Search for Senior Deep Learning Performance Architect roles in Redmond, WA, requiring 6+ years of experience, in the AI industry, with a strong focus on Python and GPU architecture.

Okay, I've searched for Senior Deep Learning Performance Architect roles in Redmond, WA, requiring 6+ years of experience, specifically in the AI industry, focusing on Python and GPU architecture. I've found 15 positions for you that match these criteria.

Senior Deep Learning Performance Architect

Redmond, WA

6 years + Experience

Python

GPU architecture

Can you help me to analyze the job description and company culture?

Sure. Here's the analysis:

Job Analysis:

The Senior Deep Learning Performance Architect role at NVIDIA fundamentally revolves around the design and analysis of performance architectures specifically tailored for deep learning applications. This position is crucial in bridging the gap between theoretical architectural designs and practical applications, ensuring that NVIDIA's offerings lead the industry in efficiency and effectiveness. Candidates will be expected to analyze hardware-software interplay, specifically how innovations in technology translate into real-world performance benefits. Core responsibilities involve a mix of developing innovative architectures and creating analytical models that gauge trade-offs in performance and power consumption. The expectation for a strong foundation in deep learning, combined with hands-on experience in GPU or ASIC architecture, is crucial as these will directly influence the speed and efficiency of AI algorithm implementations. Success in this role will likely be measured by how well these architectural advancements enhance deep learning capabilities, promoting NVIDIA's reputation as a leader in accelerated computing.

Company Analysis:

NVIDIA occupies a pioneering space within the tech industry, having shaped the graphics and artificial intelligence landscape since its inception. As a market leader, the company's strong emphasis on innovation and performance aligns seamlessly with the responsibilities of the Senior Deep Learning Performance Architect. The culture at NVIDIA seems to be fast-paced and deeply collaborative, which can foster both creativity and critical engagement across teams. Candidates must be prepared to thrive in such an environment, where cross-functional collaboration is not just encouraged but vital to success. Furthermore, the role positions the individual within a larger architectural team focusing on groundbreaking AI technologies, providing visibility with high-level stakeholders. Ultimately, this position is strategic for NVIDIA as it seeks to drive forward the next wave of advancements in deep learning and AI, meaning that the architect will play a significant part in the company’s growth trajectory and its mission to transform industries through technology.

Mock up some interview questions based on the job description.

Absolutely. Here are some mock interview questions that could come up:

Behavioral Question: Tell me about a time when you had to work with multiple teams to complete a complex project. How did you navigate differing priorities?
Behavioral Question: Describe a challenging project you worked on related to performance analysis. What was your approach, and what outcomes did you achieve?
Behavioral Question: Can you provide an example of a time when your creative thinking led to a successful solution? What was the situation and the result?
Behavioral Question: Share an experience where you had to analyze trade-offs in a project. What strategy did you use to reach a decision?
Technical Question: How would you approach developing a high-level simulator in either C++ or Python for evaluating neural network performance?
Technical Question: Can you explain your experience with performance modeling and how you’ve applied it in previous roles?
Technical Question: What specific metrics do you consider crucial when analyzing performance, power, and area trade-offs?
Technical Question: Describe your familiarity with advanced optimizations in deep learning. How have you applied these in systems you've developed?
Situational Question: Imagine you discover that a model you developed is performing below expectations after deployment. How would you approach identifying and resolving the issue?
Situational Question: Suppose you have been given conflicting feedback from hardware and software teams regarding a new architecture. How would you handle this situation?
Company Fit Question: What interests you the most about working at NVIDIA, and how do you see yourself contributing to its mission?
Company Fit Question: How do NVIDIA's values resonate with your professional experiences and aspirations?
Question for the Interviewer: What are the top challenges currently faced by the Deep Learning Architecture team?
Question for the Interviewer: How does NVIDIA measure success for someone in the role of Senior Deep Learning Performance Architect?
Question for the Interviewer: Can you share more about the collaborative culture within teams at NVIDIA and how it facilitates innovation?

Job Details

Overview Company

Senior Deep Learning Performance Architect

$184k/y-$356.5k/y

NVIDIA

6 months ago

Highlight

OnsiteFull-time6+ yearsSenior

Summary

NVIDIA is seeking a Senior Deep Learning Performance Architect to join their team in Redmond, WA. The role involves developing innovative architectures to enhance deep learning performance and efficiency.

About the Role

As a Senior Deep Learning Performance Architect, you will develop architectures to advance deep learning performance, analyze performance, cost, and power trade-offs, and collaborate with software, product, and research teams. You will also evaluate PPA for hardware features and develop high-level simulators in C++/Python.

About You

Required:

MS or PhD in Computer Science, Computer Engineering, Electrical Engineering or equivalent experience.
6+ years of relevant meaningful work experience.
Strong background in GPU or Deep Learning ASIC architecture for distributed training and/or inference.
Experience with performance modeling, architecture simulation, profiling, and analysis.
Solid foundation in machine learning and deep learning.
Strong programming skills in Python, C, C++.

Preferred:

Background with deep neural network training, inference and optimization in leading frameworks (e.g. Pytorch, JAX, TensorRT).
Familiarity with advanced optimizations and SW/HW co-design in LLM training and inference.
Exposure to using AI to accelerate SW engineering.
Demonstration of self-motivation and creative/critical thinking.

Benefits

Base salary range of $184k–$356.5k.
Eligibility for equity and benefits.

NVIDIA

Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the metaverse. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry.

Redmond, WA