Ai Deployment Manager in United States

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary We are seeking a Staff Hardware Engineer to provide advanced operational, diagnostic, and engineering support for Graphcore’s Arm-based hardware platforms across lab and data center environments. This role focuses on supporting hardware bring-up, validation, and troubleshooting of complex AI compute platforms, including server blades, racks, and rack-scale infrastructure. The successful candidate will collaborate closely with engineering, platform, and data center teams to ensure the reliability and performance of next-generation AI systems. The Team The Systems Engineering and Hardware Engineering teams are responsible for enabling the bring-up, validation, and operational reliability of Graphcore’s AI infrastructure platforms. The team works closely with server engineering, firmware teams, platform architects, and data center operations to support the development, testing, and deployment of next-generation AI compute systems. This collaborative environment enables rapid problem-solving and continuous improvement of Graphcore’s hardware platforms from early development through production deployment.

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary We are seeking a Staff Hardware Engineer to provide advanced operational, diagnostic, and engineering support for Graphcore’s Arm-based hardware platforms across lab and data center environments. This role focuses on supporting hardware bring-up, validation, and troubleshooting of complex AI compute platforms, including server blades, racks, and rack-scale infrastructure. The successful candidate will collaborate closely with engineering, platform, and data center teams to ensure the reliability and performance of next-generation AI systems. The Team The Systems Engineering and Hardware Engineering teams are responsible for enabling the bring-up, validation, and operational reliability of Graphcore’s AI infrastructure platforms. The team works closely with server engineering, firmware teams, platform architects, and data center operations to support the development, testing, and deployment of next-generation AI compute systems. This collaborative environment enables rapid problem-solving and continuous improvement of Graphcore’s hardware platforms from early development through production deployment.

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary We are seeking a Staff Hardware Engineer to provide advanced operational, diagnostic, and engineering support for Graphcore’s Arm-based hardware platforms across lab and data center environments. This role focuses on supporting hardware bring-up, validation, and troubleshooting of complex AI compute platforms, including server blades, racks, and rack-scale infrastructure. The successful candidate will collaborate closely with engineering, platform, and data center teams to ensure the reliability and performance of next-generation AI systems. The Team The Systems Engineering and Hardware Engineering teams are responsible for enabling the bring-up, validation, and operational reliability of Graphcore’s AI infrastructure platforms. The team works closely with server engineering, firmware teams, platform architects, and data center operations to support the development, testing, and deployment of next-generation AI compute systems. This collaborative environment enables rapid problem-solving and continuous improvement of Graphcore’s hardware platforms from early development through production deployment.

Own the end-to-end execution that takes NVIDIA DRIVE Autonomous Driving Software (NDAS) from product definition to production deployment across major OEM vehicle lines. We are seeking an accomplished engineering execution leader to lead adaptation, integration, validation, and production readiness of NVIDIA Autonomous driving solution (NDAS) for strategic automotive OEMs. You will work between NVIDIA product and engineering teams and the OEM's vehicle, software, systems, and validation groups. The role involves converting an agreed feature set into a deliverable vehicle program. This entails clarifying requirements, coordinating interfaces and responsibilities, setting the engineering plan, building consistent productization workflows, and managing issue resolution. You will influence teams such as systems engineering, autonomous-driving development, platform software, functional safety, cybersecurity, quality, validation, release, and customer engineering. What You'll Be Doing: Lead NDAS execution with major OEMs across the full program lifecycle — from feature definition and technical alignment through vehicle integration, validation, launch, and production ramp — owning the coordinated engineering plan per vehicle line, including requirements, architecture, adaptation scope, achievements, staffing, validation strategy, release criteria, and production-readiness gates. Translate OEM vehicle requirements and use cases into clear commitments for NVIDIA teams, while ensuring OEM partners understand product capabilities, constraints, assumptions, and the work required on their side; build scalable, repeatable workflows for adapting NDAS to specific OEM platforms, vehicle architectures, sensor configurations, compute platforms, networks, and development processes. Drive multi-functional implementation across autonomous-driving features, systems, platform software, vehicle integratio

Are you ready to contribute to world-class innovation and push the boundaries of what's possible? At NVIDIA, you'll have the opportunity to be part of a team that is driving groundbreaking impacts across various markets. As a Thermal Solutions Development Engineer, you will play a pivotal role in our Silicon Codesign Group, transforming thermal solution concepts into lab-ready builds and beyond. What you will be doing: Build thermal solutions for engineering characterization and validation of next-gen GPU/SOC products, ensuring flawless delivery from concept to lab. Drive end-to-end development and deployment of thermal solutions, collaborating with internal teams and external vendors on build requirements, prototype evaluation, test system integration, and software automation. Improve thermal design processes by incorporating feedback and findings, developing workflow and maintaining our world-class standards. Work closely with system architects, chip and board designers, and software/firmware engineers in a dynamic and high-energy environment to bring industry-defining products to market. Apply AI-enabled approaches and AI tools to accelerate design iteration, test planning, and characterization/validation triage (e.g., requirements/spec summarization, experiment prioritization, log/telemetry summarization, anomaly/outlier detection), improving cycle time, coverage, and traceability while validating outputs against physics, specs, and lab measurements. Partner with AI/tooling teams as the thermal domain SME to define use-cases, success criteria, and evaluation methods; provide feedback to improve tool reliability and usability. What we need to see:

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the role: Join our FDE team and work directly with some of the world's largest organizations to turn their most ambitious ideas into production applications on Replit. As a Forward Deployed Engineer, you'll partner closely with customers to understand their technical and business needs, architect solutions, and build the integrations and applications required to deploy Replit successfully within complex enterprise environments. This is a deeply technical and hands-on role. You won’t just advise customers on what to build—you’ll build alongside them. You’ll take applications from initial idea and prototype through deployment and production, navigate complex enterprise environments, and solve the technical challenges that emerge when AI-powered software development meets real-world infrastructure, data, security, and organizational constraints. You will: Build with Customers: Embed with strategic enterprise customers to design and build high-impact applications and AI-powered workflows on Replit, taking projects from initial concept through production deployment. Architect Enterprise Solutions: Design secure, scalable architectures that connect Replit with customers’ existing systems, data, APIs, identity providers, and infrastructure. Integrate with the customer's stack: SSO, data warehouses, internal APIs, and SaaS systems. Own Technical Deployments: Serve as the technical owner for complex enterprise implementations, identifying blockers, debugging issues, and driving projects through to successful production adoption. Bridge Customers and Product: Develop a deep understanding of how enterprises use Replit and translate field insights, technical constraints, and recurring customer needs into actionable feedback

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Vice President, Software Engineering Role Overview Mastercard is seeking a Vice President of Engineering to lead the Developer Workbench, a strategic platform designed to deliver a unified, AI-enabled, end-to-end software engineering experience across the enterprise. The Developer Workbench will bring together core engineering products, developer tools, AI-assisted coding capabilities, development environments, testing workflows, deployment pipelines, cloud development experiences, and developer insights into one cohesive platform. This leader will be accountable for transforming the Workbench from a set of disconnected tools and services into a productized developer experience that improves productivity, accelerates onboarding, increases adoption of modern engineering capabilities, and strengthens governance across the software development lifecycle. This is a senior engineering leadership role for a builder, integrator, and enterprise change leader who can operate across product, engineering, architecture, security, finance, learning, and senior technology leadership. ________________________________________ Key Responsibilities Lead the Developer Workbench Engineering Strategy • Define and execute the engineering strategy for the Developer Workbench. • Establish the technical architectu

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brain of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As a NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. NVIDIA Silicon Codesign Group is seeking a versatile engineer to join the HW bring-up methodology team. The SCG team is uniquely positioned to have an end-to-end view of the product development cycle - from early architecture definition, through bringup, to product release. What will you be doing: Led end-to-end planning and on-time execution of Nvidia's new chip bringup effort, from pre-silicon through production deployment. Coordinate multi-functional teams across Architecture, Build, Validation, DFT, SW, System, and Operations to drive shared bringup achievements. Improve cross-team communication, work, and handoffs. Develop and standardize methodologies, processes, and workflows for silicon bringup, creating reusable checklists and playbooks. Drive scheduling, equipment, and material logistics to support ambitious NPI and production schedules. Lead post-action reviews and convert learnings into concrete process improvements for future silicon and solution bringups. Contribute to post-silicon learnings that feed back into architecture, design, and pre-silicon

We are now looking for a dynamic business leader to grow NVIDIA's Host Networking business for AI infrastructure with AI Labs and Hyperscalers! This leader will drive strategic direction, customer engagement, and multi-year growth for networking products such as NVIDIA DPUs, SuperNICs, and their associated software and ecosystem. Success in this role will be measured by the level of adoption and integration of our Host Networking products with our end customers' workflows and workloads. Success is contingent upon building trust with executives, architects, product leaders, and platform teams across NVIDIA and our largest customers. This leader will lead the go-to-market motion, connecting customer AI factory needs to NVIDIA's networking portfolio and aligning product, sales, engineering, architecture, marketing, and partner teams to secure design wins and scale deployments. What you'll be doing: Identify, develop and close strategic design wins for DPU and SuperNIC with top AI labs and Cloud Service Providers! Build and implement the segment sales growth strategy for host networking across hyperscaler and frontier model AI labs building large scale AI infrastructure. Define customer-specific DPU and SuperNIC value propositions and deployment motions, and lead a matrixed team across product, architects, engineering, sales and marketing teams. Promote NVIDIA host networking products externally and internally, positioning their value for AI workloads and other infrastructure products from NVIDIA, in a collection of use-cases in Networking, Security and Storage. Build a robust opportunity pipeline with segment sales and account teams, including account mapping, customer requirements, proof points, executive engagement, and partner alignment. Track and drive quarterly business reporting, forecast accuracy, design-win progress, roadmap asks, and

The Applied AI team designs and builds algorithmically driven features in the Datadog app. We work across a range of applications, primarily focusing on analysis on streaming data such as anomaly detection, error outliers and faulty deployment analysis. As an Applied Scientist you will work on building models and algorithms for machine learning powered features within the Datadog platform. You will work closely with our engineering and product partners to explore, build, scale and deliver these features that we incubate within the Applied AI team. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Design solutions for our different use cases. You will research and benchmark relevant algorithms to find the best fit for our use-cases Leverage machine learning algorithms and statistical techniques to build new scalable product features Develop, deploy and monitor new and existing features to production Participate in our journal club by reading and presenting the latest academic research papers to the team Explore, analyze and tell the story behind high volumes of data flowing through Datadog systems Maintain and monitor the models, services and infrastructure owned by your team Participate in your team’s on-call rotation Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering, Machine Learning or related scientific field or equivalent experience You have experience working with high-scale systems and datasets including building models, applying machine learning to real business problems, and writing production data pipelines You can explain complex ideas and algorithms to non-technical audiences You care about code simplicity and performa

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. Join NVIDIA's NIM team and be part of an exceptionally ambitious project in Santa Clara, CA! As a Senior Software Engineer, NIM Tools, you will have the remarkable opportunity to build a groundbreaking model customization and deployment lifecycle platform from inception. This isn't just another feature team—you will be defining the structure for a new product surface accessed by ISVs and CSPs internationally. Your work will empower customers to take models from selection through fine-tuning, evaluation, deployment, and compliance flawlessly. What you'll be doing: Compose and build the fine-tuning handoff pipeline, including LoRA adapter repackaging, re-quantization, and re-validation into NIM. Develop the evaluation harness, ensuring models meet our high standards. Implement the observability and attestation layer to produce auditable compliance artifacts. Work in close partnership with ISVs and CSPs to roll out NVIDIA NIMs on a large scale. Define and improve durable platform APIs, steering clear of one-off integrations. Ensure flawless completion of projects through strict attention to detail and proven methodologies. Wha

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Department Introduction The Systems Integration Group (SIG) develops advanced test solutions that support semiconductor manufacturing and product quality. The team partners across engineering, operations, procurement, and external suppliers to design, build, and deploy innovative hardware platforms that enable reliable testing and validation of semiconductor devices. Join the team building semiconductor memory test platforms for tomorrow’s AI infrastructure. Position Overview As an Electrical Design Engineer, you will design and develop electronic hardware used in advanced semiconductor test systems. You will apply electrical engineering principles to create analog, digital, and mixed-signal solutions that support manufacturing and product development. This role spans the full hardware development lifecycle, from concept and design through validation, deployment, and sustaining support. You will collaborate with cross-functional teams around the world to deliver reliable, high-quality test solutions. Responsibilities Design analog, digital, and mixed-signal electronic circuits from concept through implementation and validation Evaluate and select electronic components to meet system performance, reliability, and cost objectives Develop schematics and collaborate with PCB designers to create optimized board layouts Perform circuit simulation, analysis, and design verification using industry-standard tools Debug, test, and val

We anticipate the application window for this opening will close on - 30 Sep 2026 Careers that change lives start here. Medtronic is a global leader in healthcare technology with a Mission to alleviate pain, restore health, and extend life. Our 95,000 employees work across more than 150 countries to put patients first — developing innovative medical technologies that improve the lives of 72+ million patients each year. Your unique talents will help shape the future of healthcare while building a career grounded in purpose, growth, and impact. A Day in the Life Our Automation Platforms team develops and scales reusable technologies that improve safety, quality, and productivity across Medtronic’s global manufacturing network. We're working onsite 4 days a week as part of our commitment to fostering a culture of professional growth and cross-functional collaboration as we work together to engineer the extraordinary. The person in this role will work from the Medtronic facility located in Fridley, Minnesota. This role will require 25% of travel to enhance collaboration and ensure successful completion of projects. The Sr Principal Robotics & AMR Automation Platforms Engineer will serve as the enterprise technical authority for autonomous mobile robotics, collaborative robotics, and emerging intelligent automation technologies, advancing reusable platforms from technology development through factory validation and global deployment. This role will define technical strategy, platform architectures, roadmaps, standards, and reusable capabilities while partnering with manufacturing sites, engineering teams, IT/OT, suppliers, system integrators, and Medtronic’s Surgical Robotics organization. The successful can

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. NVIDIA has a rapidly expanding ecosystem of data center platform & node designs. From single node HGX/DGX systems all the way up to large multi-node NVLink domain rack architectures. These designs have become core to NVIDIA's rapidly growing enterprise and cloud provider businesses. Each bringing together the full power of NVIDIA GPUs, NVIDIA NVLink, NVIDIA InfiniBand networking, NVIDIA Grace CPUs, and a fully optimized NVIDIA AI and HPC software stack. We’re searching for a highly motivated, technical leader to design, drive, and operationalize rack-scale factory and deployment flows for next-generation data center products. The ideal candidate will combine deep systems expertise, decisive technical leadership, and a passion for building reliable, debuggable, and scalable manufacturing and deployment solutions. What you’ll be doing: Lead and drive rack-scale/L11 flows for factory and initial data center deployment. Design and implement end-to-end factory workflows, including firmware flashing sequences, security provisioning, and deployment of software mitigations. Collaborate with data center architects, ODMs, and OEMs to define factory and data center requirements that ensure efficient and reliable production ramp. Champion reliability, debuggability an

What you’ll do Partner with medical image reconstruction scientists / engineers to build ML components that improve reconstruction quality, speed, robustness, or quantitative accuracy. Define training/evaluation pipelines, datasets, and metrics that map to user needs and design requirements. Productionize models: inference performance, reproducibility, monitoring for drift/regressions, and safe fallbacks. Collaborate on hybrid algorithms, incorporating physics and learned priors, denoisers, learned regularizers, and quality estimation. Help build tooling for rapid experimentation as well as rigorous verification of algorithm changes. What we’re looking for Strong applied ML experience plus comfort with signal processing / imaging or adjacent domains. Ability to move fluidly between research prototypes and production-quality systems. Strong evaluation discipline: metrics, ablations, data leakage avoidance, and reproducibility. A demonstrated track record of applying ML to physics-based or inverse problems (i.e., shipped projects, a portfolio, or publications.) Useful experience ML for imaging/inverse problems (or adjacent) with strong evaluation discipline and comfort with GPU performance constraints. Pragmatic production mindset: reproducible training/inference, regression testing, and safe deployment in high-stakes contexts. A background in computational physics or scientific computing. Leverage ML-based methods such as PiNNs and Neural Operators to solve partial differential equations arising in ultrasound simulation and imaging. Experience in Agentic-SciML is a plus. Hands-on experience with data curation for ML: building datasets from messy, real-world sources, defining ground truth, and managing labeling or simulation pipelines. Background in data assimilation: combining observations with physics-based models (Kalman filtering, variational methods, ensemble approaches, or learned variants).