Jobs in United States

Computer Generated Image Producer in United States

518 active opportunities · Updated October 2026

Explore current computer generated image producer jobs across United States. Filter by work mode, employment type, experience, department, date posted and distance.

O
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -82%

About the Team OpenAI, in partnership with our capital and technology partners, is building a global network of advanced datacenters to support the most demanding AI workloads. The Industrial Compute team ensures that all datacenter systems are manufactured, delivered, and commissioned to the highest standards of quality, reliability, and performance. We work closely with manufacturing partners, engineering teams, and operations staff to ensure that every component is delivered ready for installation, startup, and long-term service. About the Role We are seeking an experienced Quality Engineer (QE) to drive Product and Site Quality initiatives across OpenAI’s infrastructure ecosystem. In this role, you will establish, implement, and manage a comprehensive, quality-focused program across our global supply chain network, ensuring excellence from design through deployment. You will be responsible for end-to-end quality of finished products, as well as maintaining and elevating manufacturing site quality standards. Working cross-functionally with Design (NPI) and Engineering teams, you will help achieve First Pass Yield (FPY), quality, and reliability targets. This includes leading site and fixture validation efforts, driving yield improvement initiatives (Yield Bridge, CPI), and implementing robust corrective and preventive actions (CAPA) to resolve issues at their root cause. In addition, you will play a key role in supplier quality management, assessing and qualifying new vendors, overseeing ongoing supplier performance, and ensuring readiness for future business awards. You will lead vendor audits, monitor key performance metrics, and coordinate corrective actions to ensure predictable delivery schedules, reduced operational risk, and high system reliability. By partnering closely with external suppliers and internal Engineering and Operations stakeholders, you will help ensure OpenAI’s datacenter infrastructure is delivered on time, meets the highest quality standa

AWSRestAIGo
O
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -82%

About the Team OpenAI’s Infrastructure organization builds the systems that power frontier AI workloads at global scale. As compute demand accelerates, our ability to rapidly convert infrastructure investments into usable production capacity has become mission critical. The CPU / Storage / PoP / WAN team is responsible for the end-to-end infrastructure layers required to bring compute online: server and cluster activation, storage platforms, Points of Presence (PoPs), backbone connectivity, and global network expansion. We operate across first-party facilities, colocation environments, and strategic cloud partners to ensure OpenAI can scale reliably and quickly. About the Role We are seeking a highly technical Program Manager to lead execution across CPU, Storage, PoP, and WAN infrastructure programs that directly unlock OpenAI’s next generation compute capacity. In this role, you will own complex cross-functional programs spanning compute cluster activation, storage deployment, PoP bring-up, and backbone expansion. You will coordinate hardware readiness, site readiness, network pathing, storage availability, vendor execution, and engineering dependencies required to turn contracted infrastructure into live training and inference capacity. This role requires strong technical fluency across hardware systems, network infrastructure, storage architecture, and deployment execution. You should be comfortable operating from rack-level implementation details through executive-level capacity planning discussions. This role is based in San Francisco, CA, with travel as needed. Key Responsibilities Lead end-to-end execution of CPU / GPU cluster activation programs across OpenAI’s global infrastructure footprint Drive readiness to convert contracted compute capacity into schedulable production clusters Own deployment programs for new PoPs, backbone nodes, WAN expansion, and interconnection initiatives Build integrated schedules spanning procurement, logistics, installation, st

AWSAzureRestAI
O
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -82%

About the Team The Stargate team is responsible for building the physical infrastructure that powers large-scale AI systems. We design and deliver next-generation data centers optimized for dense compute clusters, advanced networking, and rapidly evolving hardware platforms. This work sits at the intersection of hardware engineering, systems architecture, and infrastructure execution—translating cutting-edge compute roadmaps into scalable, production-ready environments. Our teams partner across silicon vendors, server and storage OEMs, networking teams, and data center engineering organizations to bring new capacity online quickly, reliably, and at global scale. About the Role We are seeking a CPU & Storage Technical Lead to define and drive the server compute and storage architecture strategy for Stargate infrastructure. In this role, you will own technical direction across CPU platforms, memory configurations, local and disaggregated storage systems, and their integration into large-scale AI clusters. You will evaluate vendor roadmaps, lead platform tradeoff decisions, and ensure compute and storage systems are optimized for training, inference, and supporting services. You will work cross-functionally with hardware engineering, performance modeling, networking, supply chain, and deployment teams, as well as external partners such as AMD, Intel, OEMs, ODMs, and storage vendors. This is a highly strategic role for someone who can operate deeply at the component level while also driving long-range infrastructure decisions. Key Responsibilities Own CPU and storage technical strategy for Stargate compute infrastructure across current and future generations. Evaluate CPU platforms across performance, efficiency, memory bandwidth, PCIe topology, cost, and roadmap alignment. Define storage architectures for AI environments, including boot media, local NVMe, shared storage, caching tiers, metadata services, and high-performance data pipelines. Drive server platform de

AWSRestAIRust
G
📍 Austin, Texas, United States
✓ High-confidence listing
Quick readStrong listing-quality and freshness signals

About Graphcore Graphcore is a global leader in artificial intelligence computing systems. We design advanced semiconductors, software, and data center systems that provide the specialized processing power needed to advance AI while improving the efficiency required for broad adoption. As part of SoftBank Group, Graphcore belongs to a family of companies developing transformative technologies. Our U.S. engineering teams contribute to the hardware and software platforms that support the next generation of AI systems. The Opportunity We are looking for a recent graduate or early-career engineer to join the BMC Engineering team as a Graduate Firmware Engineer. You will develop low-level and embedded firmware that supports the operation, control, monitoring, and validation of advanced compute systems. You will work with experienced firmware, hardware, systems, and software engineers throughout the development lifecycle. The role combines hands-on implementation with automated testing, lab-based debugging, hardware bring-up, and analysis of interactions between firmware and the underlying platform. Start: September, 2027 Location: Austin, Texas, USA What You Will Do Design, implement, test, and maintain system and embedded firmware in C, C++, or Python. Take ownership of defined firmware features and deliver them from requirements and design through implementation, validation, and documentation. Develop and debug firmware in a Linux-based engineering environment using appropriate diagnostic tools and techniques. Create automated tests and scripts that improve firmware validation, test coverage, and engineering efficiency. Contribute to continuous integration and delivery workflows for firmware development and testing. Plan and conduct engineering experiments, analyze test data, and communicate findings clearly. Support lab setup, system configuration, hardware bring-up, and firmware validation on development platforms. Investigate firmware behavior and hardware-software

PythonLinuxArtificial IntelligenceAI
G
📍 Austin, Texas, United States
✓ High-confidence listing
Quick readStrong listing-quality and freshness signals

About Graphcore Graphcore is a global leader in artificial intelligence computing systems. We design advanced semiconductors and data center hardware that provide the specialized processing power needed to advance AI while improving the efficiency required for broad adoption. As part of SoftBank Group, Graphcore belongs to a family of companies developing transformative technologies. Our AI Engineering Campus in Austin plays an important role in building the hardware platforms that support the next generation of AI systems. The Opportunity As a Systems Engineering Intern, you will contribute to projects that combine hardware, firmware, and software engineering for advanced AI compute platforms. You will work with experienced engineers on subsystem design, laboratory testing, system validation, automation, and performance analysis. The internship provides hands-on experience with modern hardware development and system-level engineering. You will own clearly defined technical tasks with guidance from the team and document your methods, results, and conclusions. What You Will Do Support the design and testing of CPU and high-speed input and output subsystems for advanced compute platforms. Run laboratory tests and measurements to help evaluate performance, power, signal behavior, and reliability. Contribute to system-level validation by creating scripts and tools that streamline testing, data collection, and analysis. Explore emerging input and output technologies, including PCIe 6.0 and 800G Ethernet, and learn how they support advanced computing workloads. Assist with investigations into platform power, cooling, and energy efficiency, including liquid-cooling systems for high-performance processors. Use power meters, oscilloscopes, logic analyzers, or comparable lab equipment under appropriate supervision. Analyze test results, identify unexpected behavior, and work with engineers to reproduce and investigate issues. Collaborate across hardware, firmware, software, m

PythonArtificial IntelligenceAIC++
G
📍 Austin, Texas, United States
✓ High-confidence listing
Quick readStrong listing-quality and freshness signals

About Graphcore Graphcore is a global leader in artificial intelligence computing systems. We design advanced semiconductors and data center hardware that provide the specialized processing power needed to advance AI while improving the efficiency required for broad adoption. As part of SoftBank Group, Graphcore belongs to a family of companies developing transformative technologies. Our AI Engineering Campus in Austin plays an important role in building the hardware platforms that support the next generation of AI systems. The Opportunity We are looking for a recent graduate or early-career engineer to join the Hardware Platform Development team as a Graduate Systems Engineer. You will contribute to the design, integration, validation, and performance analysis of advanced AI compute platforms. You will work with experienced hardware, firmware, software, mechanical, thermal, and systems engineers throughout the development lifecycle. The role combines subsystem engineering, hands-on laboratory work, test automation, data analysis, troubleshooting, and clear technical documentation. Start: September, 2027 Location: Austin, Texas, USA What You Will Do Contribute to the design, integration, and testing of CPU and high-speed input and output subsystems for advanced compute platforms. Take ownership of defined engineering tasks from requirements and test planning through execution, analysis, and technical review. Develop system-level validation plans, procedures, scripts, and tools that improve test coverage, repeatability, data collection, and analysis. Evaluate platform performance, power, signal behavior, reliability, and interoperability using laboratory measurements and system data. Investigate emerging input and output technologies, including PCIe 6.0 and 800G Ethernet, and assess their use in advanced computing systems. Support platform power, cooling, and energy-efficiency investigations, including liquid-cooling systems for high-performance processor

PythonArtificial IntelligenceAIC++
I
📍 Oregon, Hillsboro, United States
✓ High-confidence listingCompany trend +315.4%
Quick readStrong listing-quality and freshness signals

Job Details: Job Description: Intel Corporation is the world's largest semiconductor company and a global leader in computing innovation. Our Quantum Computing Group represents Intel's bold venture into the next frontier of computing technology, leveraging our decades of semiconductor manufacturing expertise to develop silicon-based quantum processors. We're pioneering spin qubit technology in silicon quantum dots, combining cutting-edge quantum physics with Intel's unmatched manufacturing capabilities to create the world's first commercially viable quantum computers. Our collaborative approach spans Intel's research divisions and partnerships with leading academic institutions worldwide. We are seeking an exceptional Quantum Packaging Modeling Engineer to join our pioneering quantum computing team in Oregon. In this role you will be responsible for thermal modeling and simulation of various packaging solutions from silicon redistribution layers to IC substrates within a multidisciplinary team. You'll play a crucial role in advancing Intel's silicon quantum dot technology while contributing to the development of scalable quantum systems that will revolutionize computing. Key Responsibilities - Thermal modeling and simulation of packaging hardware to understand how heat flows from silicon test chips through various heat spreader hardware - Manage the overall integration of the packaging hardware and enable co-design between relevant stakeholders - Work closely with mechanical designers to define heat spreaders for optimal performance - Deliver and disseminate design milestones to stakeholders - Communicate designs in presentations and relevant documentation - Stay current with the latest developments in packaging technology and design techniques by attending conferences and rea

Recruitment
I
📍 Oregon, Hillsboro, United States
✓ High-confidence listingCompany trend +315.4%
Quick readStrong listing-quality and freshness signals

Job Details: Job Description: Intel Corporation is the world's largest semiconductor company and a global leader in computing innovation. Our Quantum Computing Group represents Intel's bold venture into the next frontier of computing technology, leveraging our decades of semiconductor manufacturing expertise to develop silicon-based quantum processors. We're pioneering spin qubit technology in silicon quantum dots, combining cutting-edge quantum physics with Intel's unmatched manufacturing capabilities to create the world's first commercially viable quantum computers. Our collaborative approach spans Intel's research divisions and partnerships with leading academic institutions worldwide. We are seeking an exceptional Quantum IC Substrate Package Layout Design Engineer to join our pioneering quantum computing team in Oregon. In this role you will be responsible for design of large form factor IC substrates within a multidisciplinary team. You'll play a crucial role in advancing Intel's silicon quantum dot technology while contributing to the development of scalable quantum systems that will revolutionize computing. Key Responsibilities - Design of IC substrates using Siemens Xpedition IC package design software - Work closely with stakeholders to meet design requirements - e.g., receive feedback from silicon testchip, signal integrity (SI), power integrity (PI), thermal simulation, and system integration engineers - Deliver and disseminate design milestones to stakeholders - Design validation and verification; including DRC and LVS - Advanced packaging design integration (2.5D and 3D) with IC substrate - Tapeout of designs with substrate suppliers in collaboration with Intel substrate teams - Communicate designs in presentations and relevant documentation - Stay curre

AIRecruitment
I
📍 Oregon, Hillsboro, United States
✓ High-confidence listingCompany trend +315.4%
Quick readStrong listing-quality and freshness signals

Job Details: Job Description: Intel Corporation is the world's largest semiconductor company and a global leader in computing innovation. Our Quantum Computing Group represents Intel's bold venture into the next frontier of computing technology, leveraging our decades of semiconductor manufacturing expertise to develop silicon-based quantum processors. We're pioneering spin qubit technology in silicon quantum dots, combining cutting-edge quantum physics with Intel's unmatched manufacturing capabilities to create the world's first commercially viable quantum computers. Our collaborative approach spans Intel's research divisions and partnerships with leading academic institutions worldwide. We are seeking an exceptional Quantum Interposer Design Engineer to join our pioneering quantum computing team in Oregon. In this role you will be responsible for physical design and integration of advanced packaging interposers within a multidisciplinary team. You'll play a crucial role in advancing Intel's silicon quantum dot technology while contributing to the development of scalable quantum systems that will revolutionize computing. Key Responsibilities - Physical design and integration of interposers used within advanced packaging for quantum computing - Work closely with stakeholders to meet design requirements - e.g., receive feedback from silicon testchip, signal integrity (SI), power integrity (PI), thermal simulation, and system integration engineers - Design validation and verification; including DRC and LVS - Deliver and disseminate design milestones to stakeholders - Communicate designs in presentations and relevant documentation - Stay current with the latest developments in packaging technology and design techniques by attending conferences and reading papers As

Recruitment
I
📍 Oregon, Hillsboro, United States
✓ High-confidence listingCompany trend +315.4%
Quick readStrong listing-quality and freshness signals

Job Details: Job Description: Intel Corporation is the world's largest semiconductor company and a global leader in computing innovation. Our Quantum Computing Group represents Intel's bold venture into the next frontier of computing technology, leveraging our decades of semiconductor manufacturing expertise to develop silicon-based quantum processors. We're pioneering spin qubit technology in silicon quantum dots, combining cutting-edge quantum physics with Intel's unmatched manufacturing capabilities to create the world's first commercially viable quantum computers. Our collaborative approach spans Intel's research divisions and partnerships with leading academic institutions worldwide. We are seeking an exceptional Quantum Packaging Signal/Power Integrity (SI/PI) Engineer to join our pioneering quantum computing team in Oregon. In this role you will be responsible for modeling and simulation of various packaging solutions from silicon redistribution layers to IC substrates within a multidisciplinary team. You'll play a crucial role in advancing Intel's silicon quantum dot technology while contributing to the development of scalable quantum systems that will revolutionize computing. Key Responsibilities - Modeling and simulation of packaging hardware including redistribution layers (e.g., interposers, RDLs), IC substrates, and silicon testchip routing - Work closely with stakeholders to meet design requirements - requirements come from both theory and hardware teams. In some pathfinding projects, you will be asked to participate in creating requirements and novel packaging hardware. - System-level modelling and simulation; end-to-end simulations to ensure designs meet system-level requirements - Deliver and disseminate design milestones to stakeholders - Communicate designs in pr

Recruitment
L
📍 Tucson, United States
✓ High-confidence listingCompany trend +500%
Quick readStrong listing-quality and freshness signals

Are you ready for your next career challenge? Leidos has an opportunity for a seasoned System Administrator at Davis Monthan AFB, AZ. Candidates must possess a current TS/SCI security clearance in order to be considered. In this role you will be responsible for overseeing JWICS operations for all Wing and subordinate unit SCIFs on site. You will also be responsible for all Site-wide JWICS Command, Control, Communications, Computers, and Intelligence (C4I) and perform JWICS specific touch maintenance to install and maintain computers, servers, and all JWICS related software and hardware. (This also includes but is not limited to account management, network storage, local authentication servers, file servers, user privileges, local group policy, local software testing, restoration operations, contingency planning, and local backups.) Ensure security patching is completed and locally downloaded, and also push JAVA, NOTAMS, and TCNO patches the AF JWICS Enterprise is unable to perform remotely. Primary Responsibilities: Work directly with users at the site and liaise daily with the ESD and ESC AF to help resolve user and network related issues as well as maintain the integrity of the Site domain. Perform investigative administration operations in support of the Cyber Security Operations Center for malware, spyware, Trojans, or unauthorized software that gets detected on any device at the Site. The position is full time daily operation and may require after hours and weekend duty via on-call support. Work autonomously with minimal oversight as well as in conjunction with multiple personnel in the fulfillment of the individual employee’s functions. Must have the ability to gather facts and use effective analytical and evaluative methods to assess information, plan the sequence of actions necessary, make sound decisions and solve a variety of security problems. Thorough understanding of their respective po

H
📍 Texas, United States of America, United States
✓ High-confidence listingCompany trend +103.7%

$105.1K – $161.8K/yr

Quick readStrong listing-quality and freshness signals

NPI Mechanical Quality Engineer Description - As part of the Personal Systems Quality organization, the NPI Mechanical Quality Engineer drives product quality and reliability throughout the NPI product development lifecycle. This role partners with cross-functional teams to evaluate designs, identify and mitigate reliability risks, drive failure analysis and root cause investigations, and implement corrective actions that improve product quality and customer experience. This role provides technical leadership in reliability test development, mechanical design assessment, and Design for Quality and Reliability (DFX) initiatives to ensure high-quality products from concept through production. Strong mechanical engineering expertise, problem-solving skills, and team collaboration are essential for success in this role. *Onsite in Spring office is required 4-days a week Responsibilities: • Provides technical analysis of compute products during NPI Phase through RFQ design proposal reviews, CAD reviews, and DFX product tear downs. • Provides advanced failure analysis, root cause identification, and corrective/preventive actions for reliability concerns and/or issues during development, manufacturing, and field operations. • Proactively addresses customer requests or issues related to mechanical reliability, ensuring timely resolution while liaising with the relevant stakeholders. • Provides consultation to product development architecture teams regarding material component selection, design risk assessment, and associated reliability test plans. • Provides NUD (new, unique, difficult) risk mitigation and test plan development and develops issue prevention. • Actively mentors less-experienced engineers in the field of mechanical reliability and contributes to their growth in the organization. Education & Expe

A
📍 United States
✓ High-confidence listingCompany trend +365.2%
Quick readStrong listing-quality and freshness signals

Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritionals and branded generic medicines. Our 122,000 colleagues serve people in more than 160 countries. JOB DESCRIPTION: Position Overview The AI Platform Engineer builds and operates the machine learning and generative AI platform used by teams across Abbott Cancer Diagnostics. You'll own the full model lifecycle in production — data and feature pipelines, training and experimentation, evaluation and promotion, serving, and monitoring — along with the platform services, compute and tooling underneath it. This is hands-on infrastructure work backed by solid platform engineering practice: making inference fast and cheap, making the path from experiment to production repeatable and auditable, and shipping interfaces other engineers can build on — in support of software that ultimately reaches patients. Essential Duties Include, but are not limited to, the following: Build and maintain data, feature, and training pipelines for ML and LLM workloads — ingestion, transformation, fine-tuning, distributed training, and reproducible experiment execution with lineage tracked from dataset and code to resulting model. Implement automated evaluation and promotion gates — performance benchmarks, regression checks, and validation criteria that determine whether a model advances toward production. Automate the model lifecycle end to end through CI/CD and GitOps: packaging, promotion across environments, progressive rollout, and rollback. Build and operate production model-serving infrastructure for LLMs and predictive models, including inference optimization, autoscaling,

PythonJavaAWSKubernetes
N
📍 Santa Clara, United States
✓ High-confidence listingCompany trend -8%
Quick readStrong listing-quality and freshness signals

We're building the platform that lets long-running autonomous agents operate safely inside NVIDIA's enterprise. These are not assistants on a developer's laptop. They are fleets of agents deployed in the cloud, running continuously at scale on shared accelerated compute. They take on real work across enterprise systems, so people get far more done than they could before. This role defines the constructs that agents are built from: the blueprints they start from, the tools, skills, and plugins that power them against enterprise data, the runtime safety harness that keeps them in bounds, and the connections into credential management, sandbox, memory, and observability. The team designs and ships these building blocks so that agent developers across the company can stand up a new agent, wire it in, and run it for days or weeks. Security and safe execution come out of the box, not something each team has to get right on its own. Today an agent runs inside a single harness. Claude, Codex, and open-source agent harnesses each work differently underneath, with their own execution model, tool interface, and telemetry shape. The platform smooths over those differences, so a single skill, safety policy, or trace works the same no matter which harness is running. We want to enable agents that act on a person's behalf, governed and secure, continuously evaluated and self-improving. These agents coordinate and hand work off to each other, with identity and policy following every hop. They route and tune themselves across harnesses from live eval signals, and get better from their own production telemetry instead of waiting on a human to retrain them. Have you run agents on a harness like Claude or Codex and hit the walls that show up when they run for real, for days, against live systems — and wanted them to learn from it on their own? We're building the platform that solves those problems once, for every team. What you'll b

PythonAIFinanceHR
N
📍 Santa Clara, United States
✓ High-confidence listingCompany trend -8%
Quick readStrong listing-quality and freshness signals

NVIDIA is seeking elite ASIC Verification Engineers to verify the design and implementation of the world’s leading SoC's and GPU's. This position offers the opportunity to have real impact in a dynamic, technology-focused company impacting product lines ranging from consumer graphics to self-driving cars and the growing field of artificial intelligence. We have crafted a team of extraordinary people stretching around the globe, whose mission is to push the frontiers of what is possible today and define the platform for the future of computing. In this position, you will help to build the high-performance processor elements that implement programmable compute and graphics functionality. What you'll be doing: As a key member of our ASIC Verification team, you will verify the design and implementation of the industry's leading GPUs You will be responsible for verification of the ASIC design, architecture, golden models and micro-architecture using advanced verification methodologies such as UVM Understand the design and implementation of your unit, define the verification scope, develop the verification infrastructure and verify the correctness of the design Collaborate with architects, designers, and pre and post silicon verification teams to accomplish your tasks What we need to see: Bachelors Degree in EE, CS or CE or equivalent experience 2+ years of relevant experience Experience in verification using random stimulus along with functional coverage and assertion-based verification methodologies Background with design and verification tools (VCS or equivalent simulation tools, debug tools like Verdi, GDB) Experience crafting test bench environments for unit and system level verification Strong background in System Verilog or similar HVL Expertise with C/C++ programmin

Artificial IntelligenceAI
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