Comptable in United States

At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. As the Senior Product Manager, Design Systems at Vanta, you'll own the product strategy and roadmap for how every team builds Vanta's interface. Your mission is to build the horizontal tooling that lets product, engineering, and design teams create consistent, high-quality user experiences faster, so they can spend more of their time on their customers. To be successful, you’ll need to have a high level of product taste and be able to set and hold the line for high quality and easy to use products. All while working closely with your engineering and design manager partners. You'll be part of Vanta's Platform organization, which builds the foundational primitives and craft layer the rest of the product is built on. This is the first dedicated Design Systems PM role at Vanta, so you'll help shape the function itself, not just the roadmap. It's a high-autonomy, highly cross-functional role at the center of how Vanta looks, feels, and scales. What you’ll do as a Senior Product Manager, Design Systems at Vanta: Own the vision and roadmap for the frontend, spanning the design system and the front-end platform, and ladder durable platform investments to company initiatives so design and engineering can focus on customers. Evolve our design system from a broad component library into smaller, composable building blocks with consistent APIs, including making components first-class for AI and LLM-driven experiences. Drive accessibility and internationalization programs to their committed milestones, including global-scale localization and meeting accessibility standards. Partner with our AI team to enable the agentic patterns product team

About the Team OpenAI’s User Operations team shepherds our customers’ adoption of AI and ensures that our customers' product experience is nothing short of exceptional. We are building the very first post-AGI support team. We resolve complex issues, provide technical guidance, and support customers in maximizing value and adoption from deploying our products. We work closely with Sales, Technical Success, Product, Engineering and others, to deliver the best possible experience to our customers at scale. OpenAI's customers represent a range of diverse backgrounds and maturity, from early-stage startups to established global enterprises. Within Premium Support, Dedicated Support Engineers combine deep technical troubleshooting with an enduring understanding of our most strategic customers’ architectures, critical workloads, and business priorities. Through proactive reliability work, ownership during incidents, and AI-powered support capabilities, we help customers operate successfully as their use of OpenAI grows. About the Role We’re looking for a senior leader to build and scale our Dedicated Support Engineering function globally. You will define its strategy, build the team, and establish how we deliver technically rigorous, proactive support for customers running some of the most complex and consequential workloads on OpenAI. This role combines organizational leadership, technical judgment, and executive customer engagement. You will establish a model in which DSEs develop deep customer context, independently advance difficult investigations, anticipate operational risks, and drive issues through resolution. You will also turn what the team learns into improvements that benefit customers across OpenAI. You should bring experience building technical organizations that maintain long-term accountability for enterprise customers. Leadership in Technical Account Management, enterprise Support Engineering, or a comparable technical customer function is particularly rel

Leidos is seeking a highly analytical and curious Data Analyst who is passionate about turning data into actionable business insights. The ideal candidate combines strong technical expertise with critical thinking and exceptional communication skills. This role requires someone who can work independently, uncover meaningful patterns in complex datasets, and communicate findings in a way that drives informed business decisions. *The Data Analyst will be a hybrid role, 50% onsite in the Fort Worth, TX office and 50% remote. The candidate for this role must be within commutable distance to the office location. Primary Responsibilities: Extract, clean, transform, and validate data from multiple sources, including relational databases. Write efficient SQL queries to retrieve, manipulate, and analyze large datasets. Develop Python-based data analysis workflows for data exploration, modeling, and reporting. Perform exploratory data analysis (EDA), including univariate, bivariate, and multivariate analysis. Apply statistical methods and predictive modeling techniques such as linear regression and other statistical evaluations. Utilize AI and machine learning tools to identify trends, generate insights, and improve analytical processes. Build and evaluate machine learning models, including: Regression Classification Clustering Decision Trees Supervised Learning Unsupervised Learning Investigate data anomalies and independently determine the root causes behind unexpected results. Identify the most relevant data elements, metrics, and business questions without requiring extensive direction. Translate complex analytical findings into clear, compelling presentations and recommen

Product Manager Enterprise Integrations Description - Role Summary We are looking for a Principal Product Manager to lead the evolution of HP’s Enterprise Integration strategy—from fragmented, point-to-point integrations to a scalable, productized API ecosystem. This role will define and drive a shift toward API-as-a-product, enabling reusable business capabilities, accelerating developer productivity, and laying the foundation for an AI-first, composable enterprise. You will play a pivotal role in transforming our integration landscape into a unified Integration Fabric, and ultimately an Intelligence Fabric that powers next-generation digital and AI-driven experiences. What You’ll Own API Productization Strategy Transform APIs from point solutions into reusable, discoverable product offerings Define capability-based packaging aligned to business domains (B2C, B2B, Partner ecosystems) Drive standardization across design, classification, and maturity frameworks Enterprise Integration Fabric Define integration patterns that unify platform, SaaS, and custom-built APIs Establish a holistic, cross-application view of enterprise APIs Reduce point-to-point integrations through reusable architecture patterns and services Data + API Convergence Partner with Data teams to define and expose data products via APIs Enable consistent access to enterprise data through standardized interfaces Align API strategy with enterprise data governance and cataloging AI-First APIs & Developer Experience Define APIs optimized for AI agents, automation, and developer productivity Build APIs that are discoverable, composable, and machine-consumable Enable next-gen use cases including agent or

Citibank, N.A. seeks a Project Management Lead for its Irving, Texas location. Duties: Manage end-to-end delivery of wholesale credit risk and climate risk initiatives, overseeing projects lifecycle from requirements intake through execution and implementation. Define and monitor project milestones, dependencies to ensure timely project delivery and resolution of emerging risks or constraints. Partner with model developers in order to streamline, consolidate and redevelop wholesale credit risk models. Support model validation, audit readiness and project success by maintaining comprehensive documentation, remediation trackers, and evidence repositories. Coordinate with technology partners to optimize model integration, leading efforts to embed Comprehensive Capital Analysis and Review (CCAR) and International Financial Reporting Standard 9 (IFRS9) models into the library system. A telecommuting/hybrid work schedule may be permitted within a commutable distance from the worksite, in accordance with Citi policies and protocols. Requirements: Requires a Master’s degree, or foreign equivalent, in Finance, Business Analytics, or related field and 4 years of experience as a Project Manager, Financial Analyst, Accountant, or related position involving treasury and balance-sheet risk assessment, wholesale credit risk management and financial audit management. 4 years of experience must include: Risk management processes and frameworks in order to measure financial exposures under stress scenarios in model development; Understanding of control framework and regulatory expectations for model documentation, validation and periodic review; Project management including project structuring, development of timeline, implementation phases planning, resources allocation, identification of dependencies and bottlenecks, and escalation of issues; Data analysis and data quality assurance, including cleanliness of the data, completeness and accuracy, while ad

As a Key Accounts Enterprise Sales Engineer, you will provide technical expertise through sales presentations, product demonstrations, and supporting technical evaluations (POVs). Sales Engineers help qualify and close opportunities with customers and partners and have a voice with the product team to help prioritize features based on input from customers, competitors, and partners. What You’ll Do: Partner with the Sales, Product/Engineering, Customer Success, Professional Services, and executive leadership to articulate the overall Datadog value proposition, vision and strategy to customers Lead technical strategy for both short-term and long-cycle pursuits by driving the end-to-end technical sales agenda for Fortune 100 and comparable prospects — from pipeline generation through purchase decision Technically close complex opportunities through advanced competitive knowledge, technical skill, and credibility Present at executive and technical forums, lead workshops, and translate technical detail to business impact for CIOs, SRE/Platform teams, security/compliance, and engineering leadership Maintain accurate notes and feedback in CRM regarding customer input both wins and losses Proactively engage and communicate with customers and Datadog business/technical teams regarding product feedback and competitive landscape Who You Are: Passionate about educating customers on observability risks that are meaningful to their business, and able to build and execute an evaluation plan with a customer Someone with strong written and oral communication skills. This role requires an ability to understand and articulate both the business benefits (value proposition) and technical advantages of our offering Experienced in programming/scripting with one or more languages (i.e. Python, Go, Java, etc.) and familiarity with DevOps practices such as CI/CD and IaC workflows Demonstrated ability to land into net new logo accounts and collaborate with prospects through long, multi-quarte

About the Team Training Runtime designs the core distributed machine-learning training runtime that powers everything from early research experiments to frontier-scale model runs. With a dual mandate to accelerate researchers and enable frontier scale, we’re building a unified, modular runtime that meets researchers where they are and moves with them up the scaling curve. Our work focuses on three pillars: high-performance, asynchronous, zero-copy tensor and optimizer-state-aware data movement; performant, high-uptime, fault-tolerant training frameworks (training loop, state management, resilient checkpointing, deterministic orchestration, and observability); and distributed process management for long-lived, job-specific and user-provided processes. We integrate proven large-scale capabilities into a composable, developer-facing runtime so teams can iterate quickly and run reliably at any scale, partnering closely with model-stack, research, and platform teams. Success for us is measured by raising both training throughput (how fast models train) and researcher throughput (how fast ideas become experiments and products). About the Role As a Training: ML Framework Engineer, you will work on improving the training throughput for our internal training framework, while enabling researchers to experiment with new ideas. This requires good engineering (for example designing, implementing, and optimizing state-of-the-art AI models), writing bug-free machine learning code (surprisingly difficult!), and acquiring deep knowledge of the performance of supercomputers. In all the projects this role pursues, the ultimate goal is to push the field forward. We’re looking for people who love optimizing performance, understanding distributed systems, and who cannot stand having bugs in their code. Since our training framework is used for large runs with massive numbers of GPUs, performance improvements here will have a large impact. This role is based in San Francisco, CA. We use a

About the Team Frontier Systems Foundations, part of Compute Foundations at OpenAI, builds the systems software foundation that turns new compute infrastructure into reliable, usable capacity for frontier model training. Our mission is to make some of the world's largest GPU clusters work reliably for frontier training. We bring new platforms and clusters online, safely maintain installed fleets, and partner with hardware, infrastructure, and research teams to resolve the system-level issues that keep jobs from running. That means building and maintaining the software closest to the machine: Linux and Ubuntu operating-system images, kernels and modules, drivers, packages and repositories, disks and boot configuration, firmware integration, provisioning, and system-level validation. We make these components reproducible, compatible, and safe to operate across heterogeneous fleets. About the Role We are looking for systems software engineers with deep Linux and host-systems experience to build, qualify, and maintain the operating-system foundation for OpenAI's frontier compute fleet. Relevant backgrounds include kernel and module development, Linux distribution or image engineering, package management, firmware and driver integration, disks and boot, and bare-metal provisioning. You'll work closely with hardware engineers, vendors, and infrastructure teams to bring up new platforms, integrate system components, and debug failures across firmware, disks, boot, operating systems, kernels, drivers, and workload interactions. Your work will directly influence how quickly new capacity becomes usable and how reliably large GPU fleets operate. You should be comfortable writing and maintaining production-quality systems software and automation, but we do not expect expertise across every layer. This is an opportunity to go deep on challenging systems problems while building the image, package, qualification, and recovery paths that power the next generation of frontier models

About the Team Training Runtime designs the core distributed machine-learning training runtime that powers everything from early research experiments to frontier-scale model runs. With a dual mandate to accelerate researchers and enable frontier scale, we’re building a unified, modular runtime that meets researchers where they are and moves with them up the scaling curve. Our work focuses on three pillars: high-performance, asynchronous, zero-copy tensor and optimizer-state-aware data movement; performant, high-uptime, fault-tolerant training frameworks (training loop, state management, resilient checkpointing, deterministic orchestration, and observability); and distributed process management for long-lived, job-specific and user-provided processes. We integrate proven large-scale capabilities into a composable, developer-facing runtime so teams can iterate quickly and run reliably at any scale, partnering closely with model-stack, research, and platform teams. Success for us is measured by raising both training throughput (how fast models train) and researcher throughput (how fast ideas become experiments and products). About the Role As a Training Performance Engineer, you’ll drive efficiency improvements across our distributed training stack. You’ll analyze large-scale training runs, identify utilization gaps, and design optimizations that push the boundaries of throughput and uptime. This role blends deep systems understanding with practical performance engineering — analyzing GPU kernel performance, collective communication throughput, investigating I/O bottlenecks, and sharding our models so we can train them at massive scale. You’ll help ensure that our clusters are running at peak performance, enabling OpenAI to train larger, more capable models with the same compute budget. This role is based in San Francisco, CA. We use a hybrid work model of three days in the office per week and offer relocation assistance to new employees. In this role, you will: Profil

We anticipate the application window for this opening will close on - 9 Oct 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 The Process Engineer II will support the development of manufacturing processes and battery designs for New Product Development at the Medtronic Energy and Component Center (MECC) for Cardiac Rhythmn Management (CRM) business. MECC supports the design, development, and production of power components used in implantable devices. At Medtronic, we bring bold ideas forward with speed and decisiveness to put patients first in everything we do. In-person exchanges are invaluable to our work. We are working onsite a minimum of 4 days per 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. This role will require less than 10% travel to enhance collaboration and ensure successful completion of projects. Responsibilities may include the following and other duties may be assigned: Work with cross-functional teams including Design, Operations, Quality, and Reliability to develop processes for batteries in a regulated industry; ensure processes and designs are compatible and in compliance with regulations Contribute to the innovation, development and/or optimization of new manufacturing concepts, processes and procedur

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

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 Mech/Thermal Platform team as a Graduate Mechanical Engineer. You will contribute to the mechanical design, thermal validation, and verification of advanced AI hardware and data center systems. You will work with experienced mechanical, thermal, hardware, and systems engineers throughout the development lifecycle. The role combines 3D computer-aided design, prototype evaluation, lab testing, data analysis, troubleshooting, and clear engineering documentation. What You Will Do Create and update mechanical parts, assemblies, and drawings using Creo or comparable 3D CAD software. Take ownership of defined mechanical design tasks from requirements and concepts through detailed design, review, release, and verification. Apply mechanical design, materials, manufacturing, heat transfer, and thermodynamics principles to engineering decisions. Develop mechanical and thermal test plans and procedures for prototypes and development systems. Set up and operate laboratory equipment, collect accurate data, analyze results, and document conclusions. Evaluate prototypes and identify mechanical, thermal, assembly, or manufacturability issues. Support design verification, troubleshooting, root-cause analysis, and implementation of verified design improvements. Maintain accurate engineering documentation, including design notes, drawings, test procedures, results, and change r

About Graphcore Graphcore is a global leader in artificial intelligence computing systems. We design advanced semiconductors and data center hardware that deliver 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 some of the world’s most transformative technologies. Our new AI Engineering Campus in Austin will play a central role in building the future of AI computing. The Opportunity As a Mechanical Engineering Intern, you will contribute to the mechanical design and thermal validation of advanced AI hardware. Working alongside experienced mechanical and thermal engineers, you will gain hands-on experience with 3D computer-aided design (CAD), laboratory setup, test development, prototype evaluation, and engineering documentation. Type: 12-week summer internship Timing: May - August (exact dates to be confirmed) Commitment: Full-time What You’ll Do Contribute to mechanical design activities using Creo or comparable 3D CAD software, including part modeling, assemblies, drawings, and design updates under the guidance of experienced engineers. Work with the thermal engineering team to develop test procedures and help set up laboratory capabilities for evaluating AI hardware. Support thermal and mechanical testing using appropriate laboratory equipment; collect, organize, and analyze test data. Assist the mechanical and thermal design teams with prototype evaluation, troubleshooting, design verification, and documentation of findings. Collaborate with cross-functional engineering partners, communicate progress and issues clearly, and follow applicable laboratory and safety procedures. What You’ll Bring Current enrollment in a bachelor's, master's, or doctoral program in mechanical engineering or a related discipline during the internship. Students in other disciplines with relevant mechanical engineering exper

Work Flexibility: Field-based The Field Clinical Specialist works using independent judgement, partners with local Account Managers to increase clinical support, education resulting in increased clinical acumen. Responsibilities Educate physicians on device handling, implantation and troubleshooting techniques related to Inari products. Develop, lead and/or facilitate training sessions and in-service education programs in the hospital environment. Identify therapy adoption opportunities in collaboration with Regional and Account Managers in local geographies. Communicate highly technical information clearly and effectively during fast-paced procedures. Act as a clinical interface between the medical community and the Company. Demonstrate ability to build and sustain credible business relationships with customers and share product expertise accordingly. Provide education and clinical support in response to the most complex field inquiries on an as-needed basis. Demonstrate a thorough understanding of all Inari products, related products and technical knowledge, trends, and players. Collaborate with product development teams to provide feedback on device features and new device development Document procedural case observations for regulatory requirements and ongoing continuous improvement Other duties as needed. Qualifications Associates degree in nursing or related clinical discipline preferred. Minimum three (3) years of equivalent combination of education, training, and hands-on experience in a cath lab, nursing, or comparable clinical environment. Proven

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary The Lead, Senior Decision Scientist serves as a strategic analytics and ideation leader supporting Payment Integrity Affordability initiatives with a primary focus on Fraud, Waste & Error (FWE) and Special Investigations Unit (SIU) programs. This role provides leadership and guidance to a team of Decision Scientists while driving the development, evaluation, and implementation of innovative opportunities that improve affordability outcomes and strengthen Payment Integrity capabilities. The Lead Decision Scientist is responsible for establishing analytical frameworks, managing ideation pipelines, defining success metrics, and identifying cross-functional opportunities that create enterprise value across Payment Integrity programs. Required Qualifications 7+ years of experience in healthcare analytics, Payment Integrity, Fraud, Waste & Error (FWE), Special Investigations, or related healthcare operations. 5+ years of experience leading analytical projects or providing technical leadership within a healthcare environment. Demonstrated experience working with healthcare claims platforms including ACAS, QNXT, HRP, or comparable systems. Experience using SAS, SQL, Python, R, or other analytical and statistical programming languages. Experience performing advanced data analysis, opportunity identification, trend analy