Support Specialist in United States

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 Senior AI Platform Engineer (DevOps) Who is Mastercard? 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 payment choices, making transactions secure, simple, smart, and accessible. Our technology and innovation, partnerships, and networks combined to deliver a unique set of products and services that help people, businesses, and governments realize their greatest potential. Our decency quotient (DQ) drives our culture and everything we do inside and outside our company. We cultivate an environment where individuals can thrive, collaborate, and contribute to innovations that power the global economy. Overview: The AI Platform Engineering team is responsible for building, operating, and evolving Mastercard's enterprise AI platforms and capabilities. Our mission is to provide scalable, secure, and reliable AI infrastructure that enables teams across Mastercard to accelerate the development and deployment of AI-powered solutions. As a Senior AI Engineer, you will help design, implement, and operate the foundational platforms that support AI and machine learning workloads across the enterprise. You will work at the intersect

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, Business Development, Global Business Platforms Vice President, Business Development, Business Platforms Overview The Global Partnerships team is responsible for cultivating and managing Mastercard’s strategic partnerships with key players across the payments ecosystem. The team works with global players in tech, e-commerce, and financial services to create innovative, differentiated products and solutions that shape the future of commerce. Through a consultative approach, and inspired by Mastercard’s longstanding focus on inclusive growth, we are passionate about working hand in hand with mission-aligned companies to solve real-world problems for people and businesses around the world. The Global Business Platforms vertical under Global Partnerships builds strategic relationships with top companies in technology, commerce, and finance that serve businesses around the globe. This team leverages Mastercard’s capabilities to solve real-world challenges and deliver seamless, secure, and inclusive payment experiences for our partners and their business customers of all sizes. We are looking for a strategic leader with strong business development and partnership expertise to lead engagement and partnerships with technology platforms serving the business space. This role will help develop a

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 Manager, Software Engineering As part of an exciting, fast paced environment developing authentication and security solutions in the e-commerce space, this position will provide technical expertise within the development lifecycle for new products and services. • Are you interested in re-defining how MasterCard does online authentication today? • Have you ever brought a product to market on a global scale? • Are you motivated to stay on cutting edge of technology? This position manages Software Engineering teams that partner with product owners, architecture, development, and operations teams to continue evolving the Mastercard Authentication platform. The role is accountable for people leadership, resourcing, delivery planning, project schedules, and vendor relationships. Role • Lead major authentication initiatives by setting technical direction, guiding architecture decisions, and ensuring engineering teams deliver secure, scalable solutions. • Partner with product, architecture, and engineering leaders to shape authentication strategy, roadmaps, and solution architectures for new and existing business opportunities. • Mentor engineers and engineering leads by providing technical guidance, coaching, and feedback that strengthen team capability and delivery outcomes. • Lead and mana

Are you ready to be part of an ambitious team driving digital transformation at NVIDIA? As a Sr. Staff Business Systems Analyst, you will play a pivotal role in crafting intuitive, high-impact experiences that support our core business functions. This outstanding opportunity offers the chance to collaborate with global partners and influence decisions that determine our competitive edge! What you’ll be doing: Design and scale AI-powered workflows, agentic experiences, and internal products that simplify work, surface relevant context, and enable employees to complete tasks more effectively across enterprise tools. Drive internal go-to-market and adoption strategies for digital and AI capabilities, including persona-based value propositions, enablement, communications, feedback loops, and outcome measurement. Apply a product mindset to develop intuitive, simple, and high-impact experiences, starting with the user problem and connecting solutions to meaningful business outcomes. Collaborate with global partners, architects, engineers, and business leaders to define product vision, prioritize capabilities, and develop world-class systems that support NVIDIA’s core business functions. Use data, user feedback, and qualitative insights to identify opportunities and make informed decisions, leveraging strong storytelling skills to build alignment and influence priorities. Build trusted relationships with collaborators at all levels; facilitate productive discussions, navigate ambiguity, and negotiate trade-offs across user needs, technical constraints, timelines, and business value. Champion employee experience and user-centric development by continuously gathering feedback and measuring adoption, usability, satisfaction, and business impact to evolve solutions after launch. What we need to see : Bachelor’

Job Title Sales, Territory Manager (Allentown/Scranton, PA) Job Description RespirTech’s Territory Manager represents the InCourage airway clearance therapy medical device, calling on but not limited to Pulmonologists to support patients with chronic respiratory and neuromuscular conditions on a journey to better breathing. Your role: Executing outside sales and territory management, inclusive of account management and new business development. Employing a hunter mentality to identify new opportunities, overcome objections and change the mindsets of prescribers, while achieving performance growth goals. Performing total office sales calls, in-services on patient profiles, product demonstrations and presenting clinical evidence to physicians. Being an expert on Medicare, Medicaid and private insurance coverage-criteria for InCourage vest therapy, while effectively educating healthcare teams in identifying patients who meet coverage criteria. Obtaining medical record documentation in order for coverage to be obtained. Analyzing data to effectively target priority healthcare teams and create sales call routing. Capable to be flexible and adjust routing to fit pipeline management needs. You're the right fit if: You’ve acquired 3+ years of successful direct field sales, clinical education or clinical sales support experience. Previous durable/home medical equipment and/or pharmaceutical sales experience preferred. Your skills include: Ability to be in the field within your territory 90% (some territories may include overnights). The ability to build and maintain strong customer relationships. You have a Bachelor’s Degree in Business Administration, Marketi

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 Infrastructure Quality 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, general contractors, engineering teams, and operations staff to ensure that every component is delivered ready for installation, startup, and long-term service. Our work spans from vendor qualification through commissioning, ensuring operational readiness across our global portfolio. About the Role We are seeking an experienced Manufacturing Quality Engineer (MQE) to establish, implement, and manage a manufacturing-focused quality program for datacenter infrastructure. This role will be responsible for vendor oversight, quality assurance, process improvement, and issue resolution for all critical systems. You will lead vendor audits, monitor performance metrics, and coordinate corrective actions to ensure predictable delivery schedules, reduced risks, and operational reliability. By partnering with vendors, construction teams, and internal stakeholders, you will help ensure OpenAI’s datacenters are delivered on time and built to the highest operational standards. Travel Domestic and international travel as needed (estimated 40–60%) to manufacturing sites, datacenter locations, and partner facilities. Key Responsibilities Vendor Oversight & Performance Management Conduct manufacturing evaluation, audits, and improve vendor performance across production, inspection, testing, and delivery phases. Develop and track quality metrics to assess manufacturing performance and identify trends. Partner with vendors to refine processes, training, and quality controls to mitigate risks before shipment. Program Development & Execution Develop and maintain a datacenter-focused m

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. Plaid’s Product team builds the network that powers open finance. At Supplier Products, we focus on building trusted, transparent experiences for financial institutions operating in Plaid’s ecosystem. Responsibilities: You will lead a team of 6 engineers, ranging from mid-level to Staff, developing them through clear goal setting, coaching, and feedback. You’ll define and drive the long-term strategy for this focus area, in close partnership with technical and product leaders across Plaid. You’ll collaborate with cross-functional partners to identify high-leverage opportunities, shape the roadmap, and dive deep into technical design and execution details to ensure consistent delivery of high-impact business outcomes. You’ll uphold a high bar for technical quality and delivery velocity, leading by example. Qualifications: 8+ years of industry experience, that includes time as a Staff-level engineer before transitioning into management. 1+ years of engineering management experience Deep experience designing scalable, reliable architectures that support real-world products at scale. Track record of building and growing high performing engineering teams (either as an engineer or a manager). Our mission

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About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We’re looking for business operations managers to join the team. This person will work closely with folks across marketing, sales, operations, and finance across a variety of initiatives to help scale the business in our next phase of growth. You'll be a generalist who gets in the weeds on all the business and operational aspects of a high-growth startup. In this role, you will: Drive in-depth quantitative analyses to inform our pricing and packaging strategy. Help spin up our deal desk and streamline enterprise deals. Support the exec team on various finance functions, from investor relations to large cloud vendor negotiations to identifying cost optimization opportunities. Implement new tools and processes to enable the GTM org to grow rapidly. Get creative on a spectrum of ad-hoc projects like securing new office space in Manhattan. Requirements: We are looking

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're hiring a Compute Strategy and Operations lead to own how Modal plans for and acquires GPU and CPU capacity. You'll size our infrastructure needs ahead of demand, source supply across hyperscalers, neoclouds, and datacenter operators, and negotiate and close the contracts to secure it. The compute you secure directly determines what Modal can sell and build. In this role, you will: Own end-to-end procurement of GPU and CPU capacity across hyperscalers, neoclouds, and datacenter operators Build and maintain a strong pipeline of supplier relationships Evaluate supply options on price, availability, hardware specs, networking capabilities, and SLA terms Negotiate and close contracts: reserved capacity agreements, spot arrangements, MSAs, DPAs, and order forms Work closely with our engineering teams to translate technical requirements into procurement specs Track

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Requirements: 5+ years of experience writing high-quality production code Experience building high-performance distributed systems at a large scale (the more battle scars, the better) Strong cloud skills Strong knowledge of low-level operating system foundations (Linux kernel, file systems, containers, etc.) Experience with performance engineering (tell us a story of when you shaved off a few milliseconds!) Ability to work in-person in our NYC or SF office. Prior experience with Rust is nice to have, but not required. Ability to participate in on-call rotation and respond to production incidents.

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: At Modal, we sell cloud services atop which our customers run their critical production systems. As a rapidly growing new cloud infrastructure company, we seek to improve our reliability dramatically while scaling the size of our platform, customer base, and our team. This role is for people who are deep systems thinkers, love stacking nines, and thrive from making others move faster at scale. Responsibilities include: Identifying architectural changes to improve reliability and performance. Fostering a culture of reliability across Modal’s engineering organization. Defining and implementing operational processes such as deployments, upgrades, etc. Operating systems like Kubernetes, Postgres, Redis, etc. Participating in on-call rotations, and responding to production incidents. Requirements: 5+ years of experience writing high-quality production code. 2+ years of

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role We're looking for an Engineering Manager to lead a team of highly experienced engineers building the infrastructure that powers Modal's serverless GPU platform. This is a hands-on leadership role — expect to split your time between technical contribution and people management depending on what the team needs. You'll set direction, remove blockers, and build a strong engineering culture as your team tackles hard problems in distributed computing, large-scale data handling, and performance optimization. Who You Are You're an experienced engineering leader who stays close to the work and builds alongside your team when it counts. You earn trust through technical depth, not title. You communicate clearly, help strong engineers move fast without cutting corners, and stay calm and pragmatic under pressure. You care as much about how your team gets to an answer as the answ

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for strong engineers with experience in making ML systems performant at scale. If you are interested in contributing to open-source projects and Modal’s container runtime to push language and diffusion models towards higher throughput and lower latency, we’d love to hear from you! Requirements: 5+ years of experience writing high-quality, high-performance code. Experience working with torch, high-level ML frameworks, and inference engines (vLLM or TensorRT). Familiarity with Nvidia GPU architecture and CUDA. Experience with ML performance engineering (tell us a story about boosting GPU performance — debugging SM occupancy issues, rewriting an algorithm to be compute-bound, eliminating host overhead, etc). Nice-to-have: familiarity with low-level operating system foundations (Linux kernel, file systems, containers, etc).