AI Developer, Technology Engineer

NVIDIA

. Develop GPU-accelerated techniques for generative AI, deep learning, and machine learning workloads .

Posted 10/2/2026full-timeUnited StatesJunior💰 $124,000 - $241,500 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in developing and optimizing GPU-accelerated techniques for generative AI and deep learning, with a strong foundation in C/C++ programming and performance tuning. Capable of collaborating with engineering teams and publishing optimization techniques in industry forums.

Highest-signal resume keywords

GPU-Accelerated Techniques DevelopmentC/C++ Programming FluencyPerformance Tuning and OptimizationParallel Programming KnowledgeTraining and Inference Frameworks Experience

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Generative AIDeep LearningMachine LearningAlgorithmsPerformance AnalysisLow-Level Software OptimizationLinear AlgebraNumerical MethodsCPU ArchitecturesGPU Architectures

Soft Skills

Good Communication SkillsOrganization SkillsLogical Problem SolvingPrioritization Skills

Certifications & Qualifications

MS in Computer SciencePhD in Relevant Field

Industry Keywords

Accelerated ComputingOpen-Source ProjectsTraining and Inference StacksServing FrameworksPre-Training PipelinesPost-Training Pipelines

Tech Stack

Tools & technologies

C++

About the role

Key responsibilities & impact

Develop GPU-accelerated techniques for generative AI, deep learning, and machine learning workloads
Optimize generative AI training and inference on NVIDIA platforms with key developers
Build and optimize algorithms and contribute to training and inference frameworks, low-level software libraries, and open-source projects
Analyze and optimize complex AI algorithms on modern CPU and GPU architectures with industry and academic experts
Collaborate with NVIDIA engineering and research teams on next-generation hardware, system software, libraries, and programming models
Publish optimization techniques in developer blogs and present at industry conferences

Requirements

What you’ll need

MS in Computer Science, Computer Engineering, or 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 comprehensive knowledge of parallel programming, performance analysis and optimization
Hands-on experience doing low-level performance optimizations
Foundational understanding of modern CPU and GPU architectures
Good communication and organization skills, with a logical approach to problem solving and prioritization skills
Experience with training and inference stacks, serving frameworks, pre-training and post-training pipelines
Strong foundation in linear algebra and numerical methods (ways to stand out)
PhD in a relevant field (ways to stand out)

Benefits

Comp & perks

Equity
Benefits 📊 Check your resume score for this job Improve your chances of getting an interview by checking your resume score before you apply. Check Resume Score