AI Developer Technology Engineer

Nvidia

Confirmed live today High trust

Hybrid

Quick summary

Work type: Hybrid
Location: Santa Clara, CAWestford, MAAustin, TXHillsboro, ORDurham, NC
Salary: $124,000–$195,500 / yr
Employment: Full-time
Posted: 2 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $176k

This role $160k

$112k most similar roles pay here $235k

This role pays less than 64% of similar roles. Most pay $146,450–$204,562 — the shaded band above. At the midpoint, this role pays about $160k versus about $176k 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 1391 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1116 roles with salary data.

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At a glance

TL;DR · AI Developer Technology Engineer

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The AI Developer Technology Engineer joins the DevTech team to accelerate the frontier of generative AI training and inference. This role involves developing cutting-edge techniques to GPU-accelerate complex workloads across large language models, diffusion models, and multimodal systems. You will work directly with developers to optimize algorithms, contribute to low-level software libraries, and influence the design of next-generation hardware and programming models. The position requires a master's degree in a related field or equivalent experience, along with at least one year of professional experience in software engineering and performance tuning. Essential skills include C/C++ programming fluency, deep knowledge of parallel programming, and advanced understanding of CPU and GPU architectures. You will solve technical bottlenecks by performing in-depth analysis of complex AI algorithms to deliver peak performance on modern hardware systems for the developer community.

Skills

C++ C GPU Machine Learning Deep Learning Parallel Programming Performance Tuning Linear Algebra Numerical Methods

What you'll do

Develop techniques to GPU-accelerate complex workloads for LLMs, diffusion models, and multimodal systems.
Optimize generative AI training and inference performance directly on the NVIDIA platform.
Build and optimize algorithms for training/inference frameworks, low-level software libraries, and open-source projects.
Perform in-depth analysis and optimization of complex AI algorithms on modern CPU and GPU architectures.
Influence the design of next-generation hardware, system software, and programming models through internal collaboration.
Publish breakthrough optimization techniques in developer blogs and present at industry conferences.

What we're looking for

MS in Computer Science, Computer Engineering, or a related computational field (or equivalent experience).
1+ years of relevant work or research experience in software engineering and performance tuning.
Programming fluency in C/C++ with a deep understanding of algorithms and software development.
Background in accelerated computing with knowledge of parallel programming, performance analysis, and optimization.
Hands-on experience performing low-level performance optimizations.
Foundational understanding of modern CPU and GPU architectures.
PhD in a relevant field (preferred).
Experience with training/inference stacks, serving frameworks, pre-training/post-training pipelines, linear algebra, and numerical methods (preferred).

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