Quality Specialist Jobs

NVIDIA is well positioned as the 'AI Computing Company', our GPUs being the brains that power modern Deep Learning software frameworks, accelerated analytics, modern data centers, and driving autonomous vehicles. We are looking for a Senior Software QA Test Development Engineer to join in the mission of crafting a distributed technology for all NVIDIA teams that remotely manage 10s of 1000s of resources in a simple and controlled fashion, allowing engineers to focus on engineering and automation, rather than being burdened by manual operational tasks. SWQA test developer engineers at NVIDIA are responsible for creating test plans, execution, and reporting, as well as developing scripts for test automation, designing and developing tools for the QA team, and developing integration tests for validation. As a test developer, you must identify weak spots and constantly design better and more creative test plans to break software and identify potential issues. You will have a huge impact on the quality of NVIDIA's products. The ideal candidate must have strong programming skills and hands-on experience using AI development tools to improve quality and productivity across the end-to-end QA workflow. This includes leveraging AI assistants for test automation, code generation, debugging, and enhancing testing efficiency. During the interview process, we will assess your ability to effectively use AI development tools and evaluate your programming capabilities to ensure you can deliver high-quality solutions. What you’ll be doing: Architect, implement, and evolve scalable agentic end to end SWQA workflow, automated test frameworks, infrastructure, and tooling for complex software products. Define test strategy and quality gates across functional, integration, regression, reliability, and release-validation workflows. Build and maintain high-value automated coverage for Linux-based, co

NVIDIA's GeForce Now, the next-generation gaming service powered by NVIDIA GPUs in the cloud, transforms a Mac, any PC, or just a mobile device into a high-performance gaming rig. GeForce NOW automatically keeps games up-to-date, and users around the globe can instantly stream the latest games in high-definition resolution at the lowest latency for the smoothest gameplay. Just click and play! Visit us at https://www.nvidia.com/en-us/geforce-now. In addition to gaming, the state-of-the-art low-latency streaming technology has expanded to a new range of applications, including augmented and virtual reality, artificial intelligence, and robotics. We are now looking for a Senior Software Engineer – Streaming with strong C++ skills and a deep interest in streaming technologies to join a team of highly skilled and motivated software engineers who help build the next generation of applications with media and data streaming capabilities. Now, are you passionate about driving this technology to its edge? Do you understand various streaming protocols? Can you solve complicated problems and propose innovative solutions? Then, we are keen to hear from you. What you’ll be doing: Design, develop, optimize, and debug C++ software for ultra low-latency streaming systems. Build and improve media streaming pipelines using technologies such as WebRTC, GStreamer, RTP/RTCP, and related protocols. Analyze CPU, memory, networking, media pipeline, and scheduling behavior across real-world workloads. Work across Windows, Linux, QNX, applications frameworks, and embedded platforms. Define and implement KPIs for networking quality, streaming quality, and user experience. Integrate streaming softwa

NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can address, and that matter to the world. This is our life’s work, to amplify human creativity and intelligence. Make the choice to join us today. Design-for-X Engineering at NVIDIA works on groundbreaking innovations involving crafting creative solutions in AI for Chip Design and AI for Predictions in various use cases in manufacturing testing on some of the industry's most complex semiconductor chips. What you'll be doing: As a senior member in our team, you will work on innovating in the DFT Power, Thermal & Voltage Noise Methodology areas. This will include working on groundbreaking low power & thermal solutions for our manufacturing tests to be enabled at conditions that push the boundaries for our datacenter GPUs. You will work with multi-functional teams including Product Development & Power Architecture, implementing brand-new methodologies on hard-to-solve problems for improving our outgoing quality of chips. You will work on post-silicon data analysis for power to architect the next-gen solutions. In addition, you will help develop and deploy DFT methodologies for our next generation products using Applied ML & Gen AI solutions. You will also help mentor junior engineers on test designs and trade-offs including cost and quality. What we need to see: BSEE (or equ

By submitting your resume, you’re expressing interest in our 2027 RDSS (Research and Development Substitute Services) program. Please confirm your eligibility with the local district office before applying the role. We are now looking for a Diagnostic NIC Software Engineer. The NPI Diag TW team is searching for Firmware Software Engineer to develop efficient secure and stable diagnostic firmware/software tools and scripts to enable factory build and debugging on NVIDIA products. In this role, engineers should be able to develop, maintain, debug CX/BF chip firmware/software and NBU Diagnostic software upon the next generation NVIDIA DGX/MGX servers, GPU baseboard, and PCIe cards. You will participate in a focused effort to develop and productize ground-breaking solutions that will be applied on many NVIDIA products. You'll find the work is exciting, fun, and meaningful. We have deadlines, customers, and competitions. We are the leading artificial intelligence computing company and are paving the way with innovations in gaming, visualization, supercomputing and self-driving cars. As a key member of our firmware team, you will be a key leader responsible for the Firmware of our DGX/GPU software stack. What you'll be doing: Be involved in the definition, architectural design, and development of security Diag tool and test coverage planning for NVIDIA DGX products with an opportunity to craft its future. Assist with defining and making sure the software development process meets security and performance standards. Design and/or make recommendations for Network solutions that apply to our software to satisfy DGX/GPU server guidelines and requirements. Design Diag tool and scripts to make sure DGX/GPU products go for production smoothly. Design Diagnostic software to help validate GPU/CPU/NIC/DPU HW with good performance and quality. <

NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can address, and that matter to the world. This is our life’s work, to amplify human creativity and intelligence. Make the choice to join us today. Design-for-Test Engineering at NVIDIA works on groundbreaking innovations involving crafting creative solutions for DFT architecture, verification and post-silicon validation on some of the industry's most complex semiconductor chips. What you'll be doing: As a senior member in our team, you will work with pre-silicon and post-silicon data analytics - visualization, insights and modeling. Design and uphold sturdy data pipelines and ETL processes for the ingestion and processing of DFX Engineering data from various origins Lead engineering efforts by collaborating with cross-functional teams (execution, analytics, data science, product) to define data requirements and ensure data quality and consistency You will work on hard-to-solve problems in the Design For Test space which will involve application of algorithm design, using statistical tools to analyze and interpret complex datasets and explorations using Applied AI methods. In addition, you will help develop and deploy DFT methodologies for our next generation products using Gen AI solutions. You will also help mentor junior engineers on test designs and trade-offs including cost and quality. What we need to see: BSEE (or equivalent experience) with 5&#43;, MSEE with 3&#43;, or PhD wi

We are seeking a Front-End Integration Engineer for the NIC Silicon group. Join our team at NVIDIA's Networking business unit and be part of the innovative build and implementation of the next generation Network Adapter Silicon chips. Contribute to the development of powerful communication devices. What You'll Be Doing: Own and maintain Continuous Integration pipelines. Monitor, complete, and fix daily and nightly CI flows in front-end build areas. These include Lint, Synthesis, Equivalence Checking and Simulation. Automate EDA Flows: Build, develop, and maintain robust automation scripts using Python, Tcl scripting, and Shell to integrate EDA tools (Synopsys, Cadence) into automated build pipelines. Manage Perforce Integration: Maintain multi-IP branch/stream strategies, manage workspace specs, complete hardware build drops, and handle release labels/tags in Perforce (Helix Core). Support Engineering Teams: Act as the primary point of contact for RTL and verification engineers to debug flow crashes, bottlenecks, environment setups, and CI failure reports. Enforce Quality Gates: Implement automated check-in and change list triggers to run sanity checks, linting, and style enforcement before code is committed to main streams. Optimize Infrastructure: Monitor compute farm resources (LSF) and storage usage to reduce pipeline runtime and improve overall execution efficiency. What We Need to See: Experience: 2&#43; years of hands-on industry experience in ASIC/SoC front-end integration, CAD, or EDA flow automation. Education: Bachelor’s degree or Master’s degree or equivalent experience in Electrical Engineering, Computer Engineering, Computer Science, or a related field. Perforce Expertise: Strong hands-on experience managing Perforce (P4 / Helix Core) streams, workspace specs, c

Job Title Remote Service Leader Job Description Job Responsibilities: • Coordinates the strategic planning and execution of large-scale service delivery initiatives, ensuring alignment with organizational goals and client expectations, while driving continuous improvement across all service operations. • Leads and manages multiple service delivery projects simultaneously, coordinating with cross-functional teams to ensure the seamless integration and delivery of services that meet or exceed customer satisfaction targets. • Works under limited supervision and contributes to development, modification, and execution of organizational policies impacting immediate operations of a business and/or region and/or function and potentially organization wide. • Coaches a group of diverse talent to develop their skills and ensure achievement of individual and team goals, and networks with key contacts outside own area of expertise and maintains strategic partnerships with external/internal stakeholders. • Acts as the primary point of contact for high-profile clients, building and nurturing long-term relationships to understand their strategic needs and ensuring that service delivery is tailored to support their business objectives. • Conducts in-depth analysis of service performance metrics, identifying critical areas for improvement, and implementing data-driven strategies to enhance service quality, efficiency, and overall customer experience. • Develops and enforces best practices, processes, and methodologies for service delivery, ensuring consistency, reliability, and scalability across all projects and service engagements. • Drives innovation in service delivery by staying abreast of industry trends, emerging technologies, and customer feedback, and incorporating these insights into the continuous enhancement of service offerings. • Collaborates with product development,

Job Title Field Service Engineer - Medical Imaging (Metro NYC / Tri-State Area) Job Description Field Service Engineer - Medical Imaging (Metro NYC / Tri-State Area) You will be responsible for customer relationship management through the effective use of technical knowledge to install, troubleshoot, service, and maintain equipment at customer sites nationally. The ideal candidate will be able to travel nationally but will be located in the greater New York City area. We expect this FSE to live within a 45-minute commute to Manhattan, with travel to other sites as required. Your role: Deliver exceptional customer service by setting clear expectations, meeting commitments and arrival times, and resolving customer issues efficiently. Build strong customer relationships by understanding their business environment while contributing to service revenue growth. Collaborate as an active member of the regional team to improve processes, identify training gaps, and share best practices. Continuously expand capabilities by learning new tools and becoming qualified across multiple modalities as needed. Complete all required administrative and compliance tasks in accordance with company, state, and federal regulations. This includes accurate documentation for timesheets, service work orders, expense reports, PMs, FCOs, installations, and adherence to quality and safety standards. Diagnose and resolve electronic, mechanical, and network-related system issues using established tools, resources, and escalation processes. Perform preventative maintenance, field changes, installations, and corrective service within required timeframes. Travel extensively (approximately 90%) with the ultimate focus being in the assigned territory to support customer sites, but will require overnight stays and air travel nationwide

Job Title Software Technologist - C# .NET Full Stack Job Description C# .NET Full Stack Developer Philips is a global leader in health technology, dedicated to improving lives through meaningful innovation. One of our core businesses, Connected Care , focuses on delivering smarter, data-driven solutions that connect patients, providers, and systems to improve outcomes and efficiency. This role sits within Hospital Patient Monitoring (HPM) , which provides advanced monitoring solutions for acute care settings. From bedside and transport monitors to centralized systems, HPM helps clinicians identify at-risk patients and intervene quickly. The position is based in Bangalore, a key hub supporting innovation and collaboration across Philips. Your role: Participate in the full software development lifecycle, from requirements analysis to deployment Design and develop scalable, secure, and maintainable applications using C# and .NET technologies Implement front-end components and integrate them with backend services Develop and execute unit, integration, and system tests to ensure quality and reliability Conduct code reviews to maintain coding standards and best practices Collaborate with DevOps teams for deployment and monitoring Diagnose and resolve software defects, ensuring optimal performance Create and maintain technical documentation (architecture diagrams, API specs, user guides) Stay updated on emerging technologies and apply innovative solutions Mentor junior developers and contribute to a culture of continuous improvement. You're the right fit if: Experience: Bachelor's Degree in Computer Science, Software Engineering, Information Technology</p

Work Flexibility: Hybrid or Onsite **23 month fixed term contract** All benefits included Hybrid, Carrigtwohill, Cork Join Our Team as a Senior Engineer, Advanced Operations Are you an experienced and innovative engineering professional with a passion for advancing cutting-edge technologies in the medical field? We are looking for a proactive, results-driven Senior Engineer to support our NPI programs working on our Patient Specific Joint Replacement portfolio. In this role, you will develop solutions to technical challenges of moderate scope and complexity, while playing a key part in leveraging engineering techniques to ensure NPI launch excellence. You will also lead continuous improvement initiatives aimed at accelerating time to market, driving cost efficiencies, and expanding margins by implementing innovative additive technologies and processes that differentiate our products and give us a competitive edge in the market. Key Responsibilities: Innovative Technology Integration: Support the integration of cutting-edge additive manufacturing technologies for joint replacement products, optimizing efficiency and precision in accordance with Stryker's new product development and design transfer procedures. Relationship Building and Mentorship: Foster productive relationships both internally and externally, playing a pivotal role in team dynamics. Provide periodic guidance and training to team members, contributing to a culture of continuous learning and growth. Quality Assurance and Product Optimization: Oversee and ensure the quality of processes and products, aligning with operational standards and material specifications to deliver superior joint replacement pro

Work Flexibility: Hybrid Job Description Lead Process Development Engineer (Senior Staff) Location: Carrigtwohill, Ireland Work Arrangement: Hybrid Join Stryker's NPI team and play a key role in developing the advanced manufacturing processes used to produce precision surgical blades that support knee replacement procedures. As a senior technical contributor, you will lead end-to-end process development activities, working directly with industrial laser welding, CNC equipment, and validation methodologies to create robust, scalable manufacturing solutions . This role combines hands-on engineering, technical leadership, and innovation to bring new manufacturing technologies from concept to production. Characterise, develop, and optimise manufacturing processes through hands-on testing, analysis, and process experimentation. What You Will Do Lead engineering projects by defining technical objectives, determining project direction, and driving successful outcomes. Lead capital equipment acquisition activities including equipment specification, supplier engagement, installation, and validation. Develop, characterise, and optimise manufacturing processes through hands-on testing, analysis, and process experimentation. Provide engineering support for new product and process introductions in accordance with established product development procedures. Ensure manufacturing processes meet product, quality, regulatory, and operational requirements. Participate in Process Failure Mode and Effects Analysis (PFMEA), Control Plans, Standard Operating Procedures (SOPs), and Production Part Approval Process (PPAP) activities. Review and approve validation documentation and support

At Franklin Templeton, we believe success is built through powerful partnerships. As a forward‑thinking asset manager, we build dynamic relationships with clients, understand their goals, and navigate complex markets together. We leverage cutting‑edge strategies and deep insights to unlock opportunities for long‑term wealth creation. Our talented, global teams bring expertise that is both broad and unique. From our welcoming, inclusive, and supportive culture to our globally diverse business, we offer opportunities not only to help you reach your potential, but also to contribute to our clients’ success. About the Department: The FTT – Operations group develops and supports products that power the daily operations of the Middle and Back Office. The team collaborates closely across functions to deliver reliable, scalable solutions that drive business efficiency. Joining this group means working in a dynamic, technically driven environment where innovation and teamwork are valued, and your contributions directly impact operational success. How You Will Add Value? Core Responsibilities: You will design and build software solutions with product owners to meet business needs. You will manage product backlogs and prioritize development tasks. You will participate in sprint and release planning activities. You will develop, test, and maintain high-quality code. You will conduct code reviews and ensure adherence to standards. You will support deployments and optimize performance. You will build full-stack applications across services, APIs, and infrastructure. You will collaborate with analysts

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and