Senior AI and Quant DevTech Engineer

Nvidia

Confirmed live today High trust

Hybrid

Quick summary

Work type: Hybrid
Location: Santa Clara, CANew York, NY
Salary: $152,000–$241,500 / yr
Employment: Full-time
Posted: 83 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $189k

This role $197k

$130k $253k

below market most similar roles pay here above market

This role pays more than 60% of similar roles. Most pay $153,684–$224,750 — the blue band above. At the midpoint, this role pays about $197k versus about $189k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 1623 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1110 roles with salary data.

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At a glance

TL;DR · Senior AI and Quant DevTech Engineer

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The Senior AI and Quant DevTech Engineer will join a team focused on the intersection of AI, high-performance computing, and financial markets. In this role, you will design and develop groundbreaking techniques to accelerate high-performance workloads by analyzing, optimizing, and scaling complex AI and HPC workloads for modern CPU and GPU architectures. You will profile and eliminate performance bottlenecks across the stack, from algorithms to kernels, while influencing the design of future hardware architectures and system software. Key requirements include a Master’s or PhD in a related field, fluency in C/C++, and strong hands-on experience with CUDA and parallel programming. You must demonstrate deep knowledge of linear algebra, CPU/GPU architecture fundamentals, and experience optimizing large-scale computational applications, including machine learning methods like Monte Carlo simulations.

Skills

CUDA C++ C GPU Architecture Parallel Programming High-Performance Computing TensorRT TensorRT-LLM cuTile AI Linear Algebra Monte Carlo simulations Inference Optimization Profiling Algorithms Software Design

What you'll do

Design and develop techniques to accelerate high-performance workloads for AI, math, and financial systems.
Analyze, optimize, and scale complex AI and HPC workloads for modern CPU and GPU architectures.
Profile and eliminate performance bottlenecks across algorithms, kernels, and system-level behaviors.
Publish and present technical work in conferences, talks, and blogs to educate the developer community.
Influence the design of future hardware architectures, system software, libraries, and programming models.
Collaborate with research, hardware, compiler, and tools teams to shape next-generation platforms.

What we're looking for

Strong hands-on experience with CUDA and parallel programming.
Deep understanding of CPU/GPU architecture fundamentals and their impact on performance.
Master’s or PhD in Computer Science, Computer Engineering, Electrical and Computer Engineering, or a related field.
Fluency in C/C++ and a solid foundation in algorithms and software design.
5+ years of relevant work or research experience.
Proven experience improving the performance of large-scale computational applications on GPUs.
Excellent understanding of linear algebra.
Experience with inference optimization, TensorRT, TensorRT-LLM, cuTile, or parallelizing machine learning methods (preferred).