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Gpu Performance Engineer Jobs in Riverside, CA (NOW HIRING)

... GPU optimization. • Ability to design scalable evaluation pipelines for vision/VLMs and agent ... performance. Preferred : • Experience with Agentic/RAG pipelines and knowledge graphs (LangChain ...

Knowledge of precision tradeoffs (FP16, bfloat16, quantization) and multi-GPU optimization ... Ability to design scalable evaluation pipelines for vision/VLMs and agent performance. The Extras ...

You will work on performance-critical software, collaborate closely with cross-functional teams ... Background in GPU-accelerated or graphics-intensive applications. Education: * BS or MS degree in ...

You will work on performance-critical software, collaborate closely with cross-functional teams ... Background in GPU-accelerated or graphics-intensive applications. Education: * BS or MS degree in ...

... performance of high frame rate machine vision systems. * Stay up to date with the latest ... Experience with hardware-software integration and optimization for embedded systems, including GPU ...

... performance of high frame rate machine vision systems. * Stay up to date with the latest ... Experience with hardware-software integration and optimization for embedded systems, including GPU ...

... performance of high frame rate machine vision systems. * Stay up to date with the latest ... Experience with hardware-software integration and optimization for embedded systems, including GPU ...

Experience with MLOps, AI infrastructure, GPU workloads, or ML deployment pipelines. * Familiarity ... We evaluate candidates and employees based on merit, qualifications, and performance, and we do not ...

Software Engineer, DevOps

Irvine, CA · On-site

$115K - $170K/yr

Experience with MLOps, AI infrastructure, GPU workloads, or ML deployment pipelines. * Familiarity ... We evaluate candidates and employees based on merit, qualifications, and performance, and we do not ...

Software Engineer, DevOps

Irvine, CA · On-site

$56.50 - $77.50/hr

Experience with MLOps, AI infrastructure, GPU workloads, or ML deployment pipelines. * Familiarity ... We evaluate candidates and employees based on merit, qualifications, and performance, and we do not ...

... performance of high frame rate machine vision systems. * Stay up to date with the latest ... Experience with hardware-software integration and optimization for embedded systems, including GPU ...

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Gpu Performance Engineer information

See Riverside, CA salary details

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How much do gpu performance engineer jobs pay per hour?

As of Jun 26, 2026, the average hourly pay for gpu performance engineer in Riverside, CA is $62.71, according to ZipRecruiter salary data. Most workers in this role earn between $51.39 and $70.96 per hour, depending on experience, location, and employer.

What are some common challenges faced by GPU Performance Engineers when optimizing graphics workloads?

GPU Performance Engineers often encounter challenges such as identifying performance bottlenecks within complex graphics pipelines, balancing resource utilization, and achieving optimal frame rates across diverse hardware configurations. They must use specialized profiling tools and collaborate closely with developers, driver engineers, and QA teams to address issues like memory bandwidth limitations or shader inefficiencies. Staying updated with rapidly evolving GPU architectures and optimizing for both current and next-generation hardware are also key aspects of the role.

What is a GPU Performance Engineer?

A GPU Performance Engineer is a specialist who analyzes, optimizes, and improves the performance of graphics processing units (GPUs). They work on identifying bottlenecks, optimizing code, and ensuring that GPU hardware and software deliver maximum efficiency and speed. Their role may involve working with drivers, firmware, and applications to enhance graphics and compute workloads. This job is essential in industries like gaming, AI, and high-performance computing where GPU efficiency directly impacts user experience and system performance.

What are the key skills and qualifications needed to thrive as a GPU Performance Engineer, and why are they important?

To thrive as a GPU Performance Engineer, you need a strong background in computer architecture, programming (C/C++), and a degree in computer science, electrical engineering, or a related field. Proficiency with GPU profiling tools (e.g., NVIDIA Nsight, AMD Radeon GPU Profiler), performance analysis frameworks, and parallel computing libraries like CUDA or OpenCL is typically required. Analytical thinking, problem-solving abilities, and effective communication are crucial soft skills for collaborating with developers and debugging performance bottlenecks. These skills and qualities are essential for optimizing GPU performance, ensuring efficient software-hardware interaction, and delivering high-quality graphics or compute solutions.

What is the difference between Gpu Performance Engineer vs Gpu Hardware Engineer?

AspectGpu Performance EngineerGpu Hardware Engineer
Primary FocusOptimizing GPU performance, benchmarking, and tuning softwareDesigning, developing, and testing GPU hardware components
Required SkillsProgramming, performance analysis, GPU architecture knowledgeHardware design, circuit analysis, FPGA/ASIC experience
Work EnvironmentSoftware development teams, labs for testing performanceHardware labs, manufacturing facilities, R&D centers
Common CertificationsNone specific, often requires computer engineering or related degreesElectrical engineering, VLSI design certifications

The Gpu Performance Engineer primarily focuses on optimizing and testing GPU software performance, while the Gpu Hardware Engineer designs and develops the physical GPU components. Both roles require a strong background in computer engineering, but differ in their core responsibilities and work environments.

What are popular job titles related to Gpu Performance Engineer jobs in Riverside, CA? For Gpu Performance Engineer jobs in Riverside, CA, the most frequently searched job titles are:
What cities near Riverside, CA are hiring for Gpu Performance Engineer jobs? Cities near Riverside, CA with the most Gpu Performance Engineer job openings:

Agentic AI/ML Engineer, Multimodal

FieldAI

Irvine, CA • On-site

Full-time

Posted 6 days ago


Job description

Job Summary:
FieldAI is transforming how robots interact with the real world by building risk-aware, reliable, and field-ready AI systems. As an AI/ML Engineer on the FiFM team, you will drive research and model development focused on multimodal data, computer vision, and agentic AI, contributing to the company's innovative initiatives in robotics.
Responsibilities:
• Train and fine-tune million- to billion-parameter multimodal models, with a focus on computer vision, video understanding, and vision-language integration.
• Track state-of-the-art research, adapt novel algorithms, and integrate them into FiFM.
• Curate datasets and develop tools to improve model interpretability.
• Build scalable evaluation pipelines for vision and multimodal models.
• Contribute to model observability, drift detection, and error classification.
• Fine-tune and optimize open-source VLMs and multimodal embedding models for efficiency and robustness.
• Build and optimize Multi-VectorRAG pipelines with vector DBs and knowledge graphs.
• Create embedding-based memory and retrieval chains with token-efficient chunking strategies.
Qualifications:
Required:
• Master’s/Ph.D. in Computer Science, AI/ML, Robotics, or equivalent industry experience.
• 2+ years of industry experience or relevant publications in CV/ML/AI.
• Strong expertise in computer vision, video understanding, temporal modeling, and VLMs.
• Proficiency in Python and PyTorch with production-level coding skills.
• Experience building pipelines for large-scale video/image datasets.
• Familiarity with AWS or other cloud platforms for ML training and deployment.
• Understanding of MLOps best practices (CI/CD, experiment tracking).
• Hands-on experience fine-tuning open-source multimodal models using HuggingFace, DeepSpeed, vLLM, FSDP, LoRA/QLoRA.
• Knowledge of precision tradeoffs (FP16, bfloat16, quantization) and multi-GPU optimization.
• Ability to design scalable evaluation pipelines for vision/VLMs and agent performance.
Preferred:
• Experience with Agentic/RAG pipelines and knowledge graphs (LangChain, LangGraph, LlamaIndex, OpenSearch, FAISS, Pinecone).
• Familiarity with agent operations logging and evaluation frameworks.
• Background in optimization: token cost reduction, chunking strategies, reranking, and retrieval latency tuning.
• Experience deploying models under quantized (int4/int8) and distributed multi-GPU inference.
• Exposure to open-vocabulary detection, zero/few-shot learning, multimodal RAG.
• Knowledge of temporal-spatial modeling (event/scene graphs).
• Experience deploying AI in edge or resource-constrained environments.
Company:
FieldAI is building general robot intelligence for the physical world. Founded in 2023, the company is headquartered in Mission Viejo, USA, with a team of 201-500 employees. The company is currently Growth Stage.