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Job DescriptionJob Description Upbound is redefining how modern infrastructure is built for the Agentic AI Era. We're the creators and primary maintainers of Crossplane, and we're building the Intelligent Control Plane-a new platform layer that makes infrastructure programmable, autonomous, and composable. Our mission is to power the AI-native enterprise with a foundational platform layer that helps teams provision, operate, and adapt infrastructure at scale-so platforms are ready for both humans and AI agents. We partner with leading cloud providers, ISVs, and open-source communities to help organizations move faster with greater confidence. Today, Upbound supports Fortune 500 companies and platform engineers across 100+ countries. Crossplane has surpassed 100M+ downloads and is used by 1,000+ teams worldwide. We're a Series B company backed by GV (formerly Google Ventures), Altimeter Capital, and Intel Capital, and we've raised $69M to date. Learn more at upbound.io. Upbound is hiring a Senior Software Engineer to help us build and operate Upbound Spaces, the multiple control plane management software at the heart of the Upbound Platform. As part of the Spaces team, you will help us scale Upbound to reliably support thousands of control planes, while also extending enterprise control plane management and operations both in the cloud and on premises. Our team is expanding, and this is the perfect opportunity for you to make a significant engineering impact in both development and production operations. What You'll Do Actively build and operate Upbound Spaces in production, troubleshooting and resolving issues across multi-tenant SaaS environments, as well as contributing to Upbound's open-source projects, including Crossplane. Take ownership of building features in high demand by Upbound's customers and deliver new functionality that will delight and amaze our users. Investigate and debug complex issues in customer environments, including multi-control plane scenarios, resource reconciliation problems, and performance bottlenecks. Communicate through thoughtful and thorough design documents for new initiatives and detailed post-incident reviews that drive system improvements. Support the full project lifecycle for highly scalable and reliable services running in a cloud environment - discovery, analysis, architecture, design, review, documentation, building, migration, automation, deployment, production-readiness, and ongoing operational support. Write and maintain Go code that interfaces with the Kubernetes API, such as operators, controllers, add-ons, etc., with a focus on observability, debuggability, and operational excellence. Deploy, manage, and troubleshoot our Kubernetes services in production, using metrics, logs, and traces to identify and resolve issues quickly. Build and maintain operational tooling for debugging customer environments, analyzing control plane health, and automating incident response. Author documentation, user guides, runbooks, and blog posts to support and promote new features that you release. Support the software release cycle for Spaces self-hosted distributions, including diagnosing issues in customer-managed deployments. Participate in on-call rotation to support Upbound Cloud, responding to incidents and driving them to resolution. What You'll Bring Have experience operating production cloud services at scale: monitoring, alerting, incident response, post-mortems, and continuous improvement of service reliability. Have strong debugging skills across distributed systems, including experience with observability tools (Prometheus, Grafana, OpenTelemetry, distributed tracing) and techniques for diagnosing issues in production environments. Have experience building and operating controllers that interact with the Kubernetes API server, including troubleshooting reconciliation loops, managing API rate limits, and optimizing controller performance. Are comfortable working directly with customers to understand, reproduce, and resolve complex technical issues in their environments. Take responsibility and ownership for solving problems even if they are outside your lane, especially during incidents affecting customer workloads. Demonstrate excellence in your work, constantly trying to improve your skills and the operational posture of the systems you build. Have empathy for customers and keep them in mind as you build solutions, understanding that reliability and debuggability are features. Realize the importance of clear communication and effective collaboration to work as a team, deliver great results, and support customers through technical challenges. Help create a safe environment where everyone can contribute, learn from failures, share on-call knowledge, and help each other grow as operators and engineers. Why Upbound? At Upbound, you'll help shape the systems and strategies that drive predictable, scalable growth in a product-led company embracing usage-based models. If you're excited to build from the ground up, work with cutting-edge cloud technologies, and directly impact how revenue is generated and scaled-this is your seat at the table. About Upbound Upbound is pioneering infrastructure platforms for the Agentic AI Era, serving Fortune 500 companies and platform engineers across more than 100 countries. The company empowers infrastructure and platform teams with Intelligent Control Planes - based on Kubernetes and Crossplane - that provision, operate, and adapt so platforms are ready for both humans and AI agents. Upbound is the creator and primary maintainer of Crossplane, the popular open-source framework for building cloud-native control planes, with over 100 million downloads and adoption by more than 1,000 teams worldwide. A Series B startup backed by GV (formerly Google Ventures), Altimeter Capital, and Intel Capital, Upbound has raised $69M to date. For more information, visit .

Job DescriptionJob DescriptionSalary: Title: Solutions Architect Department: Solutions Architecture/Sales Hours: M-F 8am-5pm CST About us IP Pathways is a premier Managed Service Provider (MSP) delivering cutting-edge, proprietary IT solutions and unwavering customer service. Since 2007, weve empowered clients to move faster, innovate boldly, and gain a competitive edge by Guiding IT Forward with creativity, excellence, and client-centric innovation. Job Summary Join our rapidly growing team at IP Pathways, where we have doubled in size over the last few years! The Solutions Architect is an architecture role that works very closely with Sales, Project Management, and Field Engineering in our organization. The ideal candidate will have a strong technical background, but also possess solid communication and consultative skills. We are seeking individuals with a strong work ethic and the desire to contribute to the growth and success of our organization. Key Responsibilities Develop solutions to solve highly complex technical and business issues Maintain a high level of proficiency and knowledge in data center technology product Participate in project planning and preparation Assist with knowledge transfer to the field engineering organization Participate in strategic meetings with senior leaders both internally and with customers Requirements Expertise and working knowledge of the following technologies: SAN/NAS technologies Virtualization platforms Microsoft infrastructure solutions WAN/LAN and wireless networks Private, public, and hybrid cloud environments Bachelors degree preferred Strong written and verbal communication skills Excellent interpersonal and customer service skills Strong documentation skills Highly organized with the ability to multitask effectively Self-motivated and able to work independently Exceptional presentation skills Minimum of 7-10 years of experience in Information Technology Consulting experience is a plus Physical Requirements Ability to rack servers, switches, and other data center equipment. Why IP Pathways? IP Pathways is an expert provider of hybrid IT solutions for small, medium, and enterprise companies by delivering world-class engineering services supported by high-touch customer service. Here are just some of the great reasons to work at IP Pathways: Competitive benefits package: Comprehensive healthcare, 100% company-paid disability and life insurance, and a 401(k) with company match. Work/life balance: IP Pathways believes in enabling families to be families. We proudly offer flexible and accommodating work schedules to meet your familys needs and obligations. Ongoing training: Looking for a company who will consistently invest in developing your skills? IP Pathways will help you continue your educational pursuits and provide opportunities to become certified in some of the most sought-after technologies. Next Steps Ready to help shape our team and be part of a company that turns IT into a strategic asset? Apply now to join IP Pathways and help us continue Guiding IT Forward. Sponsorship/Relocation Applicants must be authorized to work in the United States on a full-time basis. Sponsorship for employment visa status and relocation reimbursement are not offered for this position.

Job DescriptionJob DescriptionLightEdge Solutions is developing the IT solutions that will propel businesses forward over the next 10 years. Using a combination of shared and private/dedicated platforms, LightEdge has been successful in offering businesses alternatives that streamline operations, improve reliability and reduce costs.If you are passionate about creating real solutions that help businesses with cutting-edge technology, want to be challenged to think out of the box and be in a position where you can impact change on a daily basis, then LightEdge can offer you a dynamic corporate environment built on teamwork and personal responsibility. Lightedge is seeking a Solutions Architect with deep expertise in IBM Power Systems and IBM i environments to help customers modernize, optimize, and scale critical infrastructure platforms. This role combines technical architecture, customer engagement, and strategic solution design across enterprise hosting, hybrid cloud, storage, backup, and disaster recovery environments. The ideal candidate is comfortable leading technical discussions with customers, designing resilient IBM i and Power-based solutions, and partnering closely with Sales, Engineering, and Operations teams to deliver outcomes that align with business and operational goals. What You'll Do: Design and architect IBM Power Systems and IBM i solutions for enterprise and mid-market customers Lead infrastructure modernization, migration, backup/recovery, and disaster recovery initiatives Develop hybrid infrastructure solutions integrating colocation, managed services, cloud, and on-prem platforms Serve as the technical lead during customer discovery sessions, solution presentations, and architectural reviews Collaborate with Sales teams to align technical strategy with customer business requirements Create solution documentation, diagrams, scopes, and technical recommendations Work cross-functionally with Engineering, Product, and Delivery teams to ensure solution feasibility and operational alignment Provide technical mentorship and contribute to architectural standards and best practices What You'll Bring: 5+ years of experience in Solutions Architecture, Infrastructure Engineering, or related technical consulting roles Strong expertise with IBM Power Systems, IBM i (AS/400), PowerVM, and IBM PowerVS Experience designing and supporting enterprise storage, backup, disaster recovery, and high-availability solutions Strong understanding of enterprise infrastructure, hosting, and hybrid cloud environments Experience presenting technical solutions directly to customers and executive stakeholders Strong written and verbal communication skills with the ability to simplify complex technical concepts Preferred/Bonus Experience: x86 server infrastructure design and administration VMware virtualization platforms Public cloud platforms such as AWS or Azure Experience with managed hosting or colocation environments Familiarity with enterprise networking and security concepts With over 20 years in business, LightEdge offers a full stack of best-in-class IT services delivering flexibility, security, and control. Our solutions include premier colocation across seven purpose-built data centers spanning Des Moines, IA, Kansas City, MO, Omaha, NE, Austin, TX, and Raleigh, NC, industry-leading private Infrastructure as a Service (IaaS) and cloud platforms, and the top global security and compliance measures. Our owned and operated facilities, integrated DR solutions, and premium compliant cloud choices make up a true Hybrid Cloud Solution Center. LightEdge annually undergoes third-party audits for ISO 20000-1, ISO 27001, HIPAA, PCI-DSS 3.2, and SSAE 18 SOC 1 Type II, SOC 2 Type II and SOC 3. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

1999 Network Engineer Position Summary The Network Engineer serves as the lead technical resource for network architecture, administration, and security across both on-premises and Microsoft Azure environments. This role is heavily focused on network engineering responsibilities, including the design, support, optimization, and troubleshooting of LAN/WAN, wireless, firewall, and cloud networking solutions. As part of a collaborative and lean IT team, this individual will also provide secondary support for infrastructure-related functions such as server administration, workstation support, and occasional help desk escalation assistance during high-demand situations. Strong communication and customer service skills are essential, as this role supports both internal users and external managed service clients. Core Network Engineering Responsibilities (Primary Focus / Required Expertise) Design, implement, maintain, and troubleshoot enterprise network infrastructure utilizing Meraki and Azure networking technologies in both physical and virtual environments Develop and maintain detailed network documentation covering TCP/IP, DNS, DHCP, NAT, VLANs, subnetting, ISP redundancy, and OSI model concepts Lead network improvement initiatives focused on performance, scalability, resiliency, and security Design, deploy, and support LAN, WAN, WLAN, and MAN environments including routing and switching protocols such as BGP, OSPF, and EIGRP Configure, monitor, and troubleshoot firewalls, VPNs, ACLs, network segmentation, Spanning Tree, and RADIUS authentication Support wireless infrastructure and troubleshoot authentication methods and Wi-Fi standards including 802.11 a/b/g/n/ac/ax Perform network monitoring, performance analysis, and capacity planning using tools such as Wireshark, PRTG, SNMP, NetFlow, and Syslog Execute both scheduled and emergency maintenance on network systems and participate in outage and incident response activities Evaluate, implement, and coordinate network upgrades, changes, and reconfigurations while minimizing downtime Maintain accurate diagrams, standards, operational procedures, and technical documentation Coordinate with vendors, carriers, service providers, and ISPs regarding equipment, circuits, and support escalations Effectively manage priorities, projects, and deadlines within a small-team IT environment Operate independently with minimal supervision while serving as the primary technical resource for network-related initiatives Infrastructure & Systems Support (Secondary / Backup Responsibilities) Provide backup support and troubleshooting for Windows servers, virtualization platforms, and core infrastructure services as needed Assist with workstation deployment, maintenance, and troubleshooting during high-volume periods or staffing gaps Support onboarding and offboarding processes including account setup, access management, and hardware coordination Contribute to backup, disaster recovery, and business continuity planning for network-connected systems Help Desk & Team Collaboration (Occasional / As Needed) Serve as a Tier 3 escalation resource for advanced network and infrastructure-related support issues Assist with help desk ticket triage or incoming support calls during outages, peak activity, or staffing shortages Collaborate and cross-train with desktop support, LAN administrators, and service desk personnel to promote operational continuity Participate in the development and improvement of IT procedures, workflows, and operational standards Education & Experience Bachelor's degree or equivalent combination of education and related experience preferred 5-10 years of hands-on experience in network engineering, administration, or related infrastructure support roles Strong experience with Meraki networking technologies and Azure VNET environments is required Technical Skills To perform successfully in this role, candidates should possess experience with: Microsoft Office applications Network and infrastructure monitoring tools Database and internet-based applications Technical documentation and design software General systems administration and troubleshooting tools Certifications Preferred Azure Network Engineer Associate CompTIA Network+ CompTIA Security+ Travel Requirements Occasional local travel within the Metro Detroit area may be required. 1999 Network Engineer Position Summary The Network Engineer serves as the lead technical resource for network architecture, administration, and security across both on-premises and Microsoft Azure environments. This role is heavily focused on network engineering responsibilities, including the design, support, optimization, and troubleshooting of LAN/WAN, wireless, firewall, and cloud networking solutions. As part of a collaborative and lean IT team, this individual will also provide secondary support for infrastructure-related functions such as server administration, workstation support, and occasional help desk escalation assistance during high-demand situations. Strong communication and customer service skills are essential, as this role supports both internal users and external managed service clients. Core Network Engineering Responsibilities (Primary Focus / Required Expertise) Design, implement, maintain, and troubleshoot enterprise network infrastructure utilizing Meraki and Azure networking technologies in both physical and virtual environments Develop and maintain detailed network documentation covering TCP/IP, DNS, DHCP, NAT, VLANs, subnetting, ISP redundancy, and OSI model concepts Lead network improvement initiatives focused on performance, scalability, resiliency, and security Design, deploy, and support LAN, WAN, WLAN, and MAN environments including routing and switching protocols such as BGP, OSPF, and EIGRP Configure, monitor, and troubleshoot firewalls, VPNs, ACLs, network segmentation, Spanning Tree, and RADIUS authentication Support wireless infrastructure and troubleshoot authentication methods and Wi-Fi standards including 802.11 a/b/g/n/ac/ax Perform network monitoring, performance analysis, and capacity planning using tools such as Wireshark, PRTG, SNMP, NetFlow, and Syslog Execute both scheduled and emergency maintenance on network systems and participate in outage and incident response activities Evaluate, implement, and coordinate network upgrades, changes, and reconfigurations while minimizing downtime Maintain accurate diagrams, standards, operational procedures, and technical documentation Coordinate with vendors, carriers, service providers, and ISPs regarding equipment, circuits, and support escalations Effectively manage priorities, projects, and deadlines within a small-team IT environment Operate independently with minimal supervision while serving as the primary technical resource for network-related initiatives Infrastructure & Systems Support (Secondary / Backup Responsibilities) Provide backup support and troubleshooting for Windows servers, virtualization platforms, and core infrastructure services as needed Assist with workstation deployment, maintenance, and troubleshooting during high-volume periods or staffing gaps Support onboarding and offboarding processes including account setup, access management, and hardware coordination Contribute to backup, disaster recovery, and business continuity planning for network-connected systems Help Desk & Team Collaboration (Occasional / As Needed) Serve as a Tier 3 escalation resource for advanced network and infrastructure-related support issues Assist with help desk ticket triage or incoming support calls during outages, peak activity, or staffing shortages Collaborate and cross-train with desktop support, LAN administrators, and service desk personnel to promote operational continuity Participate in the development and improvement of IT procedures, workflows, and operational standards Education & Experience Bachelor's degree or equivalent combination of education and related experience preferred 5-10 years of hands-on experience in network engineering, administration, or related infrastructure support roles Strong experience with Meraki networking technologies and Azure VNET environments is required Technical Skills To perform successfully in this role, candidates should possess experience with: Microsoft Office applications Network and infrastructure monitoring tools Database and internet-based applications Technical documentation and design software General systems administration and troubleshooting tools Certifications Preferred Azure Network Engineer Associate CompTIA Network+ CompTIA Security+ Travel Requirements Occasional local travel within the Metro Detroit area may be required.

DTS is looking for Solution Architect (Java) for a long term contract with our direct client Position in Dimondale, MI. Top Skills & Years of Experience: 12+ years of professional experience in software/application development, with strong expertise in Java and developing enterprise-level systems. 5+ years of experience in application architecture, designing large-scale, mission-critical systems. 3+ years of hands-on experience in microservices architecture, containerization (e.g., Docker), and container orchestration (e.g., OpenShift or Kubernetes). Strong experience in designing multi-tier applications, distributed systems, and high-availability solutions. Strong understanding of REST APIs, service integration patterns, CI/CD pipelines, and secure application design. Proven expertise in modern security protocols and authentication frameworks, including OAuth 2.0, SAML, OpenID Connect, and JSON Web Tokens (JWT), with hands-on experience implementing secure and scalable identity and access management solutions across distributed systems. Role description: Required skills: 12+ years of professional experience in software/application development, with strong expertise in Java and developing enterprise-level systems. 5+ years of experience in application architecture, designing large scale, mission critical systems. 3+ years of hands on experience in microservices architecture, containerization (e.g., Docker), and container orchestration (e.g., OpenShift or Kubernetes). Strong experience in designing multi tier applications, distributed systems, and high availability solutions. Strong understanding of REST APIs, service integration patterns, CI/CD pipelines, and secure application design. Proven expertise in modern security protocols and authentication frameworks, including OAuth 2.0, SAML, OpenID Connect, and JSON Web Tokens (JWT), with hands on experience implementing secure and scalable identity and access management solutions across distributed systems. Proven expertise in full stack development, with hands-on experience spanning both front-end and back-end technologies. Strong proficiency in Java, Spring, Spring Boot, Oracle, and Hibernate/JPA. Strong front-end development skills using Angular, React, HTML5, CSS3, JavaScript, and TypeScript. Extensive experience working with relational and NoSQL databases Experience with message queuing systems, such as IBM MQ or equivalent technologies. Familiarity with Agile/Scrum methodologies and the ability to thrive in a fast-paced, iterative development environment. Strong background in DevOps practices and tools, including Git, Jenkins, Docker, Kubernetes, Maven Knowledge of Test-Driven Development (TDD) and hands-on experience with automated testing frameworks such as JUnit and Selenium. Experience using Playwright testing platform is desirable. Knowledge of AI driven code development tools (Amazon Q & Kiro) Excellent problem-solving, debugging, and analytical skills, with the ability to troubleshoot and resolve complex technical issues efficiently. Strong communication and collaboration skills, with the ability to work effectively in cross-functional teams. Responsibilities: Design, develop, and maintain full stack applications utilizing Java (Spring Boot) on the back end and modern JavaScript frameworks such as React, Angular, or Vue on the front end. Lead the development of scalable, secure, and high-performance solutions using Java-based technologies. Collaborate closely with product owners, architects, and cross-functional teams to deliver comprehensive full-stack solutions aligned with business goals. Design, develop, and consume RESTful APIs, and integrate with various third-party services and platforms. Build responsive, user-friendly UI components using modern front-end frameworks, ensuring a seamless user experience across devices. Actively contribute to DevOps practices, including continuous integration/continuous deployment (CI/CD), containerization using Docker/Kubernetes, and automated testing. Participate in Agile/Scrum ceremonies and collaborate effectively within an agile development environment. Analyze, design, document, implement, and test software solutions based on detailed user stories managed through Jira. Ensure accurate and timely time tracking for billing and reporting purposes. Work alongside product owners to understand and define complex business processes and translate them into effective technical solutions. Identify common issues and recurring patterns across applications to design reusable, scalable solutions that reduce redundancy and improve maintainability. Provide knowledge transfer and mentorship to team members, ensuring continuity and shared understanding of developed solutions. Detailed skills required: Proven ability to communicate effectively with both technical teams (developers, testers, architects) and business stakeholders (product owners, project managers, executives), ensuring alignment between business requirements and technical capabilities. Extensive experience working in Agile and Hybrid environments (Scrum, Kanban), with a strong track record of translating business requirements into actionable user stories for development teams; also familiar with traditional SDLC methodologies such as Waterfall. Strong understanding of enterprise software integration, including how applications interface with other systems and databases to support scalable and cohesive business solutions. Knowledgeable in IT infrastructure and architecture, APIs, middleware, and the evaluation of legacy versus emerging technologies in the context of software development decisions. Skilled at identifying functional and technical gaps in existing systems and designing targeted solutions whether through the development of new features, integration of third-party applications, or enhancement of legacy platforms to effectively meet business needs. DTS offers excellent compensation package. Contact: Kapil Sharma Team Lead Digital Technology Solutions

STAND 8 provides end to end IT solutions to enterprise partners across the United States and with offices in Los Angeles, New York, New Jersey, Atlanta, and more including internationally in Mexico and India. Staff Cloud Engineer This role is responsible for designing, implementing, and managing cloud infrastructure with a focus on automation, security, and cost optimization. The Staff Cloud Engineer serves as a technical leader, driving adoption of cloud strategies and engineering best practices across AWS and GCP environments. This position contributes to building scalable, resilient, and high-performing cloud solutions, including hybrid infrastructures supporting critical live and global event operations. The role also emphasizes continuous improvement, innovation, and cross-functional collaboration to deliver efficient and reliable cloud services. Location & Work Type Location: Tempe, AZ Work Type: On-site Key Responsibilities Develop and implement cloud solutions on AWS and GCP platforms, including networking, security, storage, compute, and authentication components Serve as project execution leader by estimating effort, breaking down tasks, and mentoring junior engineers to deliver projects on time and within budget Collaborate with architecture leaders to design cloud solutions addressing business needs across cloud and hybrid environments Automate cloud deployments and infrastructure provisioning using tools such as Terraform, Terragrunt, Python, and Ansible Ensure cloud security through account management, access controls, firewalls, and threat detection mechanisms Monitor infrastructure performance and cost efficiency, implementing optimizations and creating dashboards and alerts Troubleshoot and resolve cloud infrastructure and application issues, performing root cause analysis Lead post-incident reviews and implement corrective actions Provide thought leadership on cloud technologies, infrastructure as code, and industry best practices Develop proof of concepts (POCs) to evaluate new technologies and architectural patterns Participate in architecture reviews, project kickoffs, and post-mortem discussions Drive continuous improvement in processes, tools, and cloud strategies Qualifications Required: Deep understanding of Amazon Web Services (AWS) and Google Cloud Platform (GCP) including security, networking, IAM, authentication protocols, account management and application services Proven experience solving capacity challenges by utilizing dynamic scaling using containerization and/or serverless approaches, ensuring high availability and reliability with redundancy, and leveraging services like Direct Connect and/or AWS Outposts for hybrid connectivity Understand and implement various infrastructure architecture models (like centralized vs distributed) to define how resources, data, and processes are organized and managed within an organization's IT infrastructure - building and maintaining IT systems that are scalable, reliable, and secure Mastery of AWS Well Architected Framework principles Expert with troubleshooting and root cause analysis Ability to analyze systems with a high degree of detail and impact awareness Hands-on experience with at least 2 programming languages (Python, Java, C++, etc.) and experience writing infrastructure as code using Terragrunt and/or Terraform; our hands-on technical test requires both Python and Terraform Familiarity with DevOps principles Strong problem solving and analytical skills Effective communication skills, both verbal and written Proven experience with building deployment pipelines and enabling self-service Strong teamwork and willingness to collaborate with others Comfortable working with engineers to introduce new technologies and resolve technical challenges Preferred (Optional): BS or equivalent AWS Solutions Architect Professional, DevOps, SysAdmin, Networking, and/or Security certifications Google Cloud Platform and/or Azure Cloud knowledge Experience in the Media & Entertainment field Other certifications (CCIP, CCIE, Terraform, Google Cloud, Microsoft Azure, etc.) Benefits Medical coverage and Health Savings Account (HSA) through Anthem Dental/Vision/Various Ancillary coverages through Unum 401(k) retirement savings plan Paid-time-off options Company-paid Employee Assistance Program (EAP) Discount programs through ADP WorkforceNow Additional Details The base salary range for this position is $174K - $175K annually, depending on experience. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. About Us STAND 8 provides end-to-end IT solutions to enterprise partners across the United States and globally with offices in Los Angeles, Atlanta, New York, Mexico, Japan, India, and more. STAND 8 focuses on the "bleeding edge" of technology and leverages automation, process, marketing, and over fifteen years of success and growth to provide a world-class experience for our customers, partners, and employees. Our mission is to impact the world positively by creating success through PEOPLE, PROCESS, and TECHNOLOGY. Check out more at ; and reach out today to explore opportunities to grow together! 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Title: Programmer Analyst IV Location: Lansing, MI (Hybrid - 2-days onsite per week) Note: This is a W2 contract role - C2C, 1099, & 3 rd party candidates will NOT be considered The Programmer Analyst IV will design, develop, and maintain full stack applications utilizing Java (Spring Boot) on the back-end and modern JavaScript frameworks, such as React, Angular, or Vue on the front-end. Additionally, they will; Lead the development of scalable, secure, and high-performance solutions using Java-based technologies Collaborate closely with product owners, architects, and cross-functional teams to deliver comprehensive full-stack solutions aligned with business goals Design, develop, and consume RESTful APIs, and integrate with various third-party services and platforms Build responsive, user-friendly UI components using modern front-end frameworks, ensuring a seamless user experience across devices Actively contribute to DevOps practices, including continuous integration/continuous deployment (CI/CD), containerization using Docker/Kubernetes, and automated testing Participate in Agile/Scrum ceremonies and collaborate effectively within an Agile development environment Analyze, design, document, implement, and test software solutions based on detailed user stories managed through Jira Ensure accurate and timely time tracking for billing and reporting purposes Work alongside product owners to understand and define complex business processes and translate them into effective technical solutions Identify common issues and recurring patterns across applications to design reusable, scalable solutions that reduce redundancy and improve maintainability Provide knowledge transfer and mentorship to team members, ensuring continuity and shared understanding of developed solutions Position Qualifications: 10+ years of professional experience in software/application development, with strong expertise in Java and developing enterprise-level systems 3+ years of hands on experience in microservices architecture, containerization (e.g., Docker), and container orchestration (e.g., OpenShift or Kubernetes) Strong experience in designing multi tier applications, distributed systems, and high availability solutions Strong understanding of REST APIs, service integration patterns, CI/CD pipelines, and secure application design Proven expertise in modern security protocols and authentication frameworks, including OAuth 2.0, SAML, OpenID Connect, and JSON Web Tokens (JWT), with hands on experience implementing secure and scalable identity and access management solutions across distributed systems Proven expertise in full stack development, with hands-on experience spanning both front-end and back-end technologies Strong proficiency in Java, Spring, Spring Boot, Oracle, and Hibernate/JPA Strong front-end development skills using Angular, React, HTML5, CSS3, JavaScript, and TypeScript Extensive experience working with relational and NoSQL databases Experience with message queuing systems, such as IBM MQ or equivalent technologies Familiarity with Agile/Scrum methodologies and the ability to thrive in a fast-paced, iterative development environment Strong background in DevOps practices and tools, including Git, Jenkins, Docker, Kubernetes, Maven Expert-level proficiency in Core Java, Multithreading, Collections, Concurrency, and JVM performance tuning Knowledge of Test-Driven Development (TDD) and hands-on experience with automated testing frameworks such as JUnit and Selenium; experience using Playwright testing platform preferred Knowledge of AI driven code development tools (Amazon Q & Kiro) Excellent problem-solving, debugging, and analytical skills, with the ability to troubleshoot and resolve complex technical issues efficiently Proven ability to communicate effectively with both technical teams (developers, testers, architects) and business stakeholders (product owners, project managers, executives), ensuring alignment between business requirements and technical capabilities Extensive experience working in Agile and Hybrid environments (Scrum, Kanban), with a strong track record of translating business requirements into actionable user stories for development teams; familiarity with traditional SDLC methodologies, such as Waterfall, preferred Strong understanding of enterprise software integration, including how applications interface with other systems and databases to support scalable and cohesive business solutions Knowledgeable in IT infrastructure and architecture, APIs, middleware, and the evaluation of legacy versus emerging technologies in the context of software development decisions Skilled at identifying functional and technical gaps in existing systems and designing targeted solutions whether through the development of new features, integration of third-party applications, or enhancement of legacy platforms to effectively meet business needs A minimum of a Bachelor's Degree in a relevant field Note: This is a W2 contract role - C2C, 1099, & 3 rd party candidates will NOT be considered .

Be a part of our mission! As a world leader in creating comfortable, sustainable, and efficient climate solutions for buildings, homes and transportation, it's our responsibility to put the planet first. For us at Trane Technologies , and through our businesses including Trane and Thermo King , sustainability is not just how we do business-it is our business. Do you dare to look at the world's challenges and see impactful possibilities? Do you want to contribute to making a better future? If the answer is yes, we invite you to consider joining us in boldly challenging what's possible for a sustainable world. Learn about our benefits designed for you to Thrive at work and at home. We boldly go. Where is the work: Monday to Thursday, work onsite with your colleagues. Fridays, choose your work location, balancing what your work requires. What's in it for you: A sustainable future demands ongoing digital advancement. Our digital solutions team leads the way in developing next-generation climate technology focused on reducing demand-side energy consumption and emissions. Our team-including BrainBox AI, Nuvolo, and more-combines technical expertise with advanced analytics to create data-driven solutions that add real value for customers, communities, and the planet. Whether you're advancing AI in HVAC or driving analytics for greater efficiency, your ideas will help engineer solutions for stronger communities and a sustainable world. Trane Technologies is currently seeking a Senior Software Engineer for our Digital Solutions Team at Trane Technologies. In this cloud-first, AI-driven engineering environment, you'll join our Digital Solutions team and play a key role in transforming our flagship proprietary software. You'll help modernize a core technology platform-introducing advanced cloud architectures and unlocking the power of machine learning and artificial intelligence to deliver smarter, more sustainable climate solutions. This is an opportunity to directly influence the future of our digital product portfolio, shaping solutions at the intersection of data, cloud, and AI for critical applications in buildings, homes, and transportation. You'll collaborate across global, cross-functional teams, leveraging cutting-edge development practices and participating in a culture of innovation and continuous learning. We're looking for a hands-on, team-oriented engineer who thrives on complex problem solving, architectural design, and creating intelligent logic for real-world customer needs. Success in this role will rely on your curiosity, diligence, technical leadership, awareness of industry best practices, and your commitment to quality, security and customer success. You'll be empowered to help define and deliver truly next-generation technologies for a more sustainable world What you will do: Design, develop, and deploy highly scalable and reliable cloud-based applications, integrating AI and machine learning to deliver innovative solutions for customers. Build, maintain, and iterate on both front-end (React) and back-end (Python or Node.js) components as part of modern, user-focused web applications. Collaborate with product owners, data scientists, and UI/UX designers to create seamless, intuitive, and visually appealing interfaces. Architect and implement robust, secure microservices and APIs on AWS or similar cloud platforms. Develop and optimize data pipelines for big data and analytics, leveraging modern data stores such as columnar databases. Apply best practices for application security, scalability, and performance in a cloud-centric environment. Champion DevOps methodologies-including CI/CD, automated testing, monitoring, and infrastructure as code-to ensure rapid and reliable delivery. Work closely with global teams in an Agile environment, mentoring peers and contributing to code reviews. Stay up to date with emerging technologies, frameworks, and trends in AI, cloud, and full stack development. What you will bring: Bachelor's or Master's degree in Computer Science, Engineering, or STEM related field. 5 years of hands-on software development experience, including building, testing, and deploying cloud-native solutions. Proven full stack engineering expertise with React for front-end and Python or Node.js for back-end development. Strong UI development skills, with a demonstrated ability to deliver user-friendly, accessible, and responsive web interfaces. Extensive experience with AWS or other major cloud platforms (Azure, GCP), including leveraging managed services for scaling, security, and automation. Working knowledge of big data, analytics platforms, and columnar databases. Solid background in application security best practices within a cloud environment. Proficiency with DevOps tools and practices (CI/CD, Docker, Kubernetes, infrastructure as code, cloud monitoring). Experience collaborating within cross-functional Agile teams and effectively communicating technical concepts. Experience integrating and deploying AI/ML models into production applications is a plus. Passion for continuous learning and driving innovation through technology. Annual Base Salary Range or Hourly Base Pay Range: $127,110.00 - $177,870.00 Compensation Type: Salary Incentive Eligible: No Sales Commission Eligible: No Disclaimer : We strive to provide competitive compensation for this position, tailored to a variety of factors. The actual compensation will depend on elements such as seniority, merit, geographic location, education, experience, travel requirements, and union designation. Our compensation range is generally based on the national average for the country. Additionally, benefits may vary depending on the region, business alignment, union involvement, and employee status. Safety Sensitive Role: No The company designates certain roles as Safety Sensitive. Safety Sensitive roles may require that you pass additional drug screening. We offer competitive compensation and comprehensive benefits and programs. We are an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, pregnancy, age, marital status, disability, status as a protected veteran, or any legally protected status.5c143e31-5e48-4549-b2d185386

DivIHN (pronounced "divine") is a CMMI ML3-certified Technology and Talent solutions firm. Driven by a unique Purpose, Culture, and Value Delivery Model, we enable meaningful connections between talented professionals and forward-thinking organizations. Since our formation in 2002, organizations across commercial and public sectors have been trusting us to help build their teams with exceptional temporary and permanent talent. Visit us at to learn more and view our open positions. Please apply or call one of us to learn more For further inquiries regarding the following opportunity, please contact our Talent Specialist, Amit at or Vijay at Title: Endpoint Engineer - Hybrid (2 Openings) Duration: 6 Months Location: Onsite, Palo Alto, CA Only W2 candidates are eligible for this position. Third-party or C2C candidates will not be considered. Role Summary This is an onsite contract role based at client's Palo Alto Headquarters. The Endpoint Engineer is responsible for the design, implementation, and ongoing management of the organizations device ecosystem. This role focuses on automating the lifecycle of hardware and virtual desktops to ensure a seamless, secure, and zero-touch experience for our global workforce. You will serve as the subject matter expert for Apple and Windows management and our cloud desktop infrastructure. Technical Environment Apple (macOS and iOS): Jamf Pro Windows and Android: Microsoft Intune / Endpoint Manager Virtual Desktop: Amazon WorkSpaces (AWS) Scripting: PowerShell, Bash, Python Key Responsibilities 1. Unified Endpoint Management (UEM) Daily Operations: Perform daily upkeep, system maintenance, and regular patch management for all managed endpoints to ensure security and stability. Service Desk Escalation: Serve as the final point of contact and subject matter expert for service desk escalations related to complex endpoint issues. Apple Fleet: Architect and maintain the Jamf Pro environment for all macOS and iOS devices. Manage configuration profiles, policies, and patch management. Windows and Android: Lead the administration of Microsoft Intune, ensuring robust policy application, security baselines, and application delivery. Provisioning: Manage Apple Business Manager (ABM) and Windows Autopilot to deliver a true zero-touch deployment experience. 2. Virtual Desktop Infrastructure (VDI) Administer and optimize Amazon WorkSpaces. Manage WorkSpaces directories, custom bundles, and image creation/maintenance. Troubleshoot connectivity and performance issues within the AWS ecosystem. 3. Automation and Engineering Develop and maintain sophisticated scripts in PowerShell and Bash to automate manual tasks and integrate system APIs. Build and maintain a library of packaged software (dmg, pkg, msi) for silent deployment. Implement automated reporting for hardware inventory, license compliance, and security auditing. 4. Security and Compliance Enforce endpoint security standards, including FileVault/BitLocker encryption and EDR agent health. Partner with Security teams to remediate vulnerabilities across the endpoint fleet. Required Qualifications Experience: Minimum 3-5 years in an Endpoint Engineering or MDM-focused role. Jamf Mastery: Proven experience managing both macOS and iOS at scale via Jamf Pro. Intune Proficiency: Experience managing Windows environments through Microsoft Endpoint Manager. VDI Expertise: Hands-on experience with Amazon WorkSpaces administration. BYOD Deployment: Experience deploying and managing a Bring Your Own Device (BYOD) program for personal mobile phones (iOS/Android). Advanced Scripting: Ability to write and debug Bash and PowerShell scripts from scratch. Identity: Understanding of Okta or Azure AD (Entra ID) as it relates to device enrollment and SSO. Education and Certifications Bachelors degree in Computer Science, IT, or equivalent professional experience. Relevant certifications (e.g., Jamf 200/300, Microsoft MD-102, or AWS Certified Cloud Practitioner) are a plus. Bonus: AI Tool Deployment Experience As client continues to expand its AI-powered workforce tooling, experience deploying and managing enterprise AI tools is a strong differentiator for this role. Candidates with hands-on experience rolling out any of the following will stand out: Enterprise AI Search and Knowledge Tools Experience deploying Glean or similar AI-powered enterprise search platforms, including connector configuration, SSO integration (Okta/Azure AD), and end-user onboarding at scale. Agentic AI Coding Tools Familiarity with deploying Claude Code or GitHub Copilot to engineering teams including managing licensing, IDE plugin distribution via MDM (Jamf/Intune), and API key or credential management through secure vaulting solutions. AI Productivity and Workflow Automation Tools Experience rolling out AI desktop or productivity agents such as Claude Cowork, including packaging and silent deployment, managing update cadences, and coordinating with IT Security to ensure compliance with data handling policies. General AI Deployment Best Practices Understanding of the endpoint and identity considerations unique to AI tools: network allowlisting for LLM API endpoints, DLP policy tuning for AI-generated content, user provisioning workflows, and communicating rollout plans across IT, Security, and end-user teams. About us: DivIHN, the 'IT Asset Performance Services' organization, provides Professional Consulting, Custom Projects, and Professional Resource Augmentation services to clients in the Mid-West and beyond. The strategic characteristics of the organization are Standardization, Specialization, and Collaboration. DivIHN is an equal opportunity employer. DivIHN does not and shall not discriminate against any employee or qualified applicant on the basis of race, color, religion (creed), gender, gender expression, age, national origin (ancestry), disability, marital status, sexual orientation, or military status. IOS, macOS, VDI Expertise, BYOD

Senior Technology Development Operations ManagerCooley is seeking a Senior DevOps Manager to join the Infrastructure & Development Operations team.Position summary: The Senior Technology Development Operations (DevOps)Manageris responsible for leading the team thatdesigns, architects,deploys, tests,maintains,and documents the DevOps technology stack. This stack is responsible for facilitating a secure, CI/CD-enabled, and highly availableSaaS-baseddelivery and hosting environment for Cooley's custom applications. The Senior DevOps Manager will build and deploy green-field solutions where needed, and otherwise willprimarilywork to improve theefficiency,security,and availability/reliability of the enterprise DevOps and related infrastructure. This role will workin an integrated fashion with the development teams to build in-depth knowledge of the products and code, attending daily stand-ups as needed. In addition to being technically advanced, this position will use a high degree of emotional intelligence and the ability to work as a team towards complex and layered objectives. Specific duties and responsibilities include, but are not limited to, the following:Position responsibilities: Provide experienced leadership in developing solutions for highly scalable, highly available, hybrid cloud (IaaS, PaaS, SaaS) infrastructure patterns and platform integrations across physical colocations and hyperscalers (AWS and Azure) Manage, build, configure, administer, operate, and maintain all components that comprise our DevOps environment Leverage industry standard Frameworks and Blueprints as a foundation to create best-in-class Terraform IaC module libraries Lead the evolution of our DevOps and DevSecOps practice maturity Act as a key member of the infrastructure architecture team to identify optimization opportunities throughout the infrastructure Define, document, and enforce configuration standards and governance through IaC Develop, test, deploy, and optimize DevOps IaC code deployment pipelines and practices Provision automation using CI/CD (DevOps Pipelines) and IaC (Terraform) tooling Serve as a technical escalation point Work with our development and data teams to integrate products into a DevOps-managed environment Develop and maintain scripts to automate tool/service deployments to our Hybrid Cloud environment through DevOps Pipelines and Releases Participate in software releases and deployments Contribute to the design, update, refinement, and documentation of operational processes Provide technical mentorship and educate team members as a subject matter expert on IaC, containerization, and CI/CD Brainstorm new ideas and ways to improve product delivery and efficiency Consult peer teams for feedback during the design, testing, and implementation stages Serve as direct supervisor and mentor to direct reports Provide day-to-day supervision of direct reports, ensure compliance with assigned work hours and monitor for compliance with all firm and department policies. Manage staffing coverage, review and process time logs/time off requests Support business professional development and continued educational opportunities In collaboration with immediate supervisor and HR, participate in hiring, performance appraisals, counseling, termination and other employee lifecycle events All other duties as assigned or requiredSkills and experience:Required: After orientation at Cooley LLP, exhibit proficiency in the Microsoft Office suite, iManage and other firm applications Ability to work extended and/or weekend hours, as required Ability to travel, as required 7+ years of relevant experience in cloud infrastructure and DevOps with 2+ years of exempt/management experience in relevant roles Proficiency in AWS or Azure architecture, configuration, and security Skilled in CI/CD pipeline design using Azure DevOps, Jenkins, or GitHub Actions Strong Terraform expertise, including advanced workflows and tools like Terragrunt Experience with Docker, Kubernetes, Helm, and GitOps tools (Flux, ArgoCD) Familiarity with microservices deployment and release automation Hands-on with .NET Core containers on Linux and scripting in Linux/Windows Knowledge of open-source and NoSQL databases (e.g., MS SQL, MongoDB, Elasticsearch) Experience with APM tools (Datadog, New Relic, etc.) and IaC security tools (Snyk, tfsec)Preferred: Bachelor's Degree in Computer Science, Information Technology, Engineering, or associated discipline Experience working with advanced ETL data workflows including technologies such as AWS EMR, Azure Synapse, Azure Data Factory, or Apache Hive/Spark/Airflow Supervisory experience Experience with IaC deployment of AKS/EKS/GKE architecture is highly desired Experience with enterprise Data Lake environments using technologies such as DataBricks or SnowflakeCompetencies: Expert analytical/quantitative, problem-solving, and deductive reasoning skills, with experience performing advanced troubleshooting and root cause analysis of complex technical issues Excellent organizational, planning, and time management skills and ability to work either independently or in a team environment to manage competing priorities and meet deadlines Advanced verbal and written communication skills with the ability to present findings, conclusions, alternatives, and information clearly and concisely Experience working with all levels of staff, management, stakeholders, and vendors with ability to build effective relationships through trust and diplomacyCooley offers a competitive compensation and excellent benefits package and is committed to fair and equitable employment practices.EOE.The expected annual pay range for this position with a full-time schedule is $180,000 - $255,000. Please note that final offer amount will be dependent on geographic location, applicable experience and skillset of the candidate.We offer a full range of elective benefits including medical, health savings account (with applicable medical plan), dental, vision, health and/or dependent care flexible spending accounts, pre-tax commuter benefits, life insurance, AD&D, long-term care coverage, backup care for children and/or adults and other parental support benefits. In addition to elective benefit options, benefited employees receive firm-paid life insurance, AD&D, LTD, short term medical benefits as well as 21 days of Paid Time Off ("PTO") and 10 paid holidays each year. We provide generous parental leave and fertility benefits. New employees will attend a detailed benefit orientation to learn more about our many benefits and resources.

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you'll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation). Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming languages like Python, Scala, or Java. Basic Qualifications: Bachelor's degree At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 2 years of experience building, scaling, and optimizing ML systems Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience building production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code 2+ years of experience with data gathering and preparation for ML models 2+ years of people leader experience 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Sales Territory: $175,800 - $200,700 for Lead Machine Learning Engineer McLean, VA: $193,400 - $220,700 for Lead Machine Learning Engineer Richmond, VA: $175,800 - $200,700 for Lead Machine Learning Engineer New York, NY: $211,000 - $240,800 for Lead Machine Learning Engineer Anytown, IL: $175,800 - $200,700 for Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Senior Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you'll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation). Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming languages like Python, Scala, or Java. Basic Qualifications: Bachelor's degree At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 3 years of experience building, scaling, and optimizing ML systems At least 2 years of experience leading teams developing ML solutions Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing performant, resilient, and maintainable code 3+ years of experience with data gathering and preparation for ML models 3+ years of people management experience ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents 3+ years of experience building production-ready data pipelines that feed ML models Ability to communicate complex technical concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $225,400 - $257,200 for Sr. Lead Machine Learning Engineer New York, NY: $245,900 - $280,600 for Sr. Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Senior Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you'll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation). Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming languages like Python, Scala, or Java. Basic Qualifications: Bachelor's Degree At least 4 years of experience programming with Python, Scala, or Java (Internship experience does not apply) At least 3 years of experience designing and building data-intensive solutions using distributed computing At least 2 years of on-the-job experience with an industry recognized ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow) At least 1 year of experience productionizing, monitoring, and maintaining models Preferred Qualifications: 1+ years of experience building, scaling, and optimizing ML systems 1+ years of experience with data gathering and preparation for ML models 2+ years of experience developing performant, resilient, and maintainable code Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience with distributed file systems or multi-node database paradigms Contributed to open source ML software Authored/co-authored a paper on a ML technique, model, or proof of concept 3+ years of experience building production-ready data pipelines that feed ML models Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $158,600 - $181,000 for Senior Machine Learning Engineer New York, NY: $173,000 - $197,400 for Senior Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Senior Manager, Software Engineering, Machine Learning - Capital One Software (Remote) Ever since our first credit card customer in 1994, Capital One has recognized that technology and data can enable even large companies to be innovative and personalized. As one of the first large enterprises to go all-in on the public cloud, Capital One needed to build cloud and data management tools that didn't exist in the marketplace to enable us to operate at scale in the cloud. And in 2022, we publicly announced Capital One Software and brought our first B2B software solution, Slingshot, to market. Building on Capital One's pioneering adoption of modern cloud and data capabilities, Capital One Software is helping accelerate the data management journey at scale for businesses operating in the cloud. If you think of the kind of challenges that companies face - things like data publishing, data consumption, data governance, and infrastructure management - we've built tools to address these various needs along the way. Capital One Software will continue to explore where we can bring our solutions to market to help other businesses address these same needs going forward. As a Capital One Machine Learning Engineer (MLE), you'll be part of software team dedicated to producing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you'll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation). Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming languages like Python, Scala, or Java. Basic Qualifications: Bachelor's degree At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 3 years of experience building, scaling, and optimizing ML systems At least 2 years of experience leading teams developing ML solutions At least 4 years of people management experience. Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing performant, resilient, and maintainable code 3+ years of experience with data gathering and preparation for ML models Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform 3+ years of experience building production-ready data pipelines that feed ML models Ability to communicate complex technical concepts clearly to a variety of audiences ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $204,900 - $233,800 for Sr. Mgr, Machine Learning Engineering Richmond, VA: $204,900 - $233,800 for Sr. Mgr, Machine Learning Engineering Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Senior Manager, Software Engineering, Full Stack - Capital One Software (Remote) Ever since our first credit card customer in 1994, Capital One has recognized that technology and data can enable even large companies to be innovative and personalized. As one of the first large enterprises to go all-in on the public cloud, Capital One needed to build cloud and data management tools that didn't exist in the marketplace to enable us to operate at scale in the cloud. And in 2022, we publicly announced Capital One Software and brought our first B2B software solution, Slingshot, to market. Building on Capital One's pioneering adoption of modern cloud and data capabilities, Capital One Software is helping accelerate the data management journey at scale for businesses operating in the cloud. If you think of the kind of challenges that companies face - things like data publishing, data consumption, data governance, and infrastructure management - we've built tools to address these various needs along the way. Capital One Software will continue to explore where we can bring our solutions to market to help other businesses address these same needs going forward. We are seeking top tier talent to join our pioneering team and propel us towards our destination. You will be joining a team of innovative product, tech, and design leaders that tirelessly seek to question the status quo. As a Capital One Senior Software Manager you'll have the opportunity to be on the forefront of building this business and bring these tools to market. What You'll Do: Lead a team of developers with deep experience in distributed microservices, and full stack systems to create robust, cloud native, resilient, and highly scalable solutions in data management and security domains Is an inspirational leader, has a talent growth strategy by attracting and retaining talent, involved heavily in hiring process and practice, continues to create high levels of energy and motivation through challenges and obstacles, and proactively manages all talent by actively coaching and improving the performance of directs Has a strong engineering and technology background with the ability to learn quickly and go deep into our product and engineering solutions Help accelerate adoption of the very best engineering practices, while maintaining knowledge on industry innovations, trends and practices to curate a continual stream of incubated projects and create rapid product prototypes Promote a culture of engineering excellence and being well-managed, using opportunities to reuse and innersource solutions where possible. Lead the craftsmanship, availability, resilience, and scalability of your solutions Be the guiding force for stakeholders in design and architecture discussions, helping the engineering teams make key technology choices, and staying associated with the use case through its development lifecycle Effectively communicate with and influence key stakeholders across the enterprise at all levels of the organization. Proven collaborator and have the ability to build very strong partnerships with others to gain the trust and confidence of those around them, from hands on engineers to executives Basic Qualifications: Bachelor's Degree At least 8 years of experience in software engineering (Internship experience does not apply) At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud) At least 4 years of people management experience Preferred Qualifications: Master's Degree 10+ years of experience in software engineering in one or more of the following: GoLang, Java, Python, React, Rust, or C++ 3+ years of experience in two or more of the following: GoLang, Java, Python, Lua, React, Nginx, Rust, or C++ 5+ years of experience with AWS, GCP, Azure, or another cloud service 2+ years of experience with containerization technologies 4+ years of experience in open source frameworks 5+ years of people management experience 2+ years of experience in Big Data, Data Security, Governance and Controls 2+ years of experience in front-end development 2+ years of experience in Agile practices Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $204,900 - $233,800 for Sr. Mgr, Software Engineering Richmond, VA: $204,900 - $233,800 for Sr. Mgr, Software Engineering Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Senior Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you'll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation). Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming languages like Python, Scala, or Java. Basic Qualifications: Bachelor's degree At least 4 years of experience programming with Python, Scala, or Java (Internship experience does not apply) At least 3 years of experience designing and building data-intensive solutions using distributed computing At least 2 years of on-the-job experience with an industry recognized ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow) At least 1 year of experience productionizing, monitoring, and maintaining models Preferred Qualifications: 1+ years of experience building, scaling, and optimizing ML systems 1+ years of experience with data gathering and preparation for ML models 2+ years of experience developing performant, resilient, and maintainable code Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience with distributed file systems or multi-node database paradigms Contributed to open source ML software Authored/co-authored a paper on a ML technique, model, or proof of concept 3+ years of experience building production-ready data pipelines that feed ML models Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $158,600 - $181,000 for Senior Machine Learning Engineer Richmond, VA: $144,200 - $164,600 for Senior Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you'll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation). Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming languages like Python, Scala, or Java. Basic Qualifications: Bachelor's degree At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 2 years of experience building, scaling, and optimizing ML systems Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience building production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code 2+ years of experience with data gathering and preparation for ML models 2+ years of people leader experience 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $193,400 - $220,700 for Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Senior Manager, Software Engineering, Full Stack - Capital One Software (Remote) Ever since our first credit card customer in 1994, Capital One has recognized that technology and data can enable even large companies to be innovative and personalized. As one of the first large enterprises to go all-in on the public cloud, Capital One needed to build cloud and data management tools that didn't exist in the marketplace to enable us to operate at scale in the cloud. And in 2022, we publicly announced Capital One Software and brought our first B2B software solution, Slingshot, to market. Building on Capital One's pioneering adoption of modern cloud and data capabilities, Capital One Software is helping accelerate the data management journey at scale for businesses operating in the cloud. If you think of the kind of challenges that companies face - things like data publishing, data consumption, data governance, and infrastructure management - we've built tools to address these various needs along the way. Capital One Software will continue to explore where we can bring our solutions to market to help other businesses address these same needs going forward. We are seeking top tier talent to join our pioneering team and propel us towards our destination. You will be joining a team of innovative product, tech, and design leaders that tirelessly seek to question the status quo. As a Capital One Senior Software Manager you'll have the opportunity to be on the forefront of building this business and bring these tools to market. What You'll Do: Lead a team of developers with deep experience in distributed microservices, and full stack systems to create robust, cloud native, resilient, and highly scalable solutions in data management and security domains Is an inspirational leader, has a talent growth strategy by attracting and retaining talent, involved heavily in hiring process and practice, continues to create high levels of energy and motivation through challenges and obstacles, and proactively manages all talent by actively coaching and improving the performance of directs Has a strong engineering and technology background with the ability to learn quickly and go deep into our product and engineering solutions Help accelerate adoption of the very best engineering practices, while maintaining knowledge on industry innovations, trends and practices to curate a continual stream of incubated projects and create rapid product prototypes Promote a culture of engineering excellence and being well-managed, using opportunities to reuse and innersource solutions where possible. Lead the craftsmanship, availability, resilience, and scalability of your solutions Be the guiding force for stakeholders in design and architecture discussions, helping the engineering teams make key technology choices, and staying associated with the use case through its development lifecycle Effectively communicate with and influence key stakeholders across the enterprise at all levels of the organization. Proven collaborator and have the ability to build very strong partnerships with others to gain the trust and confidence of those around them, from hands on engineers to executives Basic Qualifications: Bachelor's Degree At least 8 years of experience in software engineering (Internship experience does not apply) At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud) At least 4 years of people management experience Preferred Qualifications: Master's Degree 10+ years of experience in software engineering in one or more of the following: GoLang, Java, Python, React, Rust, or C++ 3+ years of experience in two or more of the following: GoLang, Java, Python, Lua, React, Nginx, Rust, or C++ 5+ years of experience with AWS, GCP, Azure, or another cloud service 2+ years of experience with containerization technologies 4+ years of experience in open source frameworks 5+ years of people management experience 2+ years of experience in Big Data, Data Security, Governance and Controls 2+ years of experience in front-end development 2+ years of experience in Agile practices Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $204,900 - $233,800 for Sr. Mgr, Software Engineering Richmond, VA: $204,900 - $233,800 for Sr. Mgr, Software Engineering Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you'll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation). Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming languages like Python, Scala, or Java. Basic Qualifications: Bachelor's degree At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 2 years of experience building, scaling, and optimizing ML systems Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience building production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code 2+ years of experience with data gathering and preparation for ML models 2+ years of people leader experience 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Sales Territory: $175,800 - $200,700 for Lead Machine Learning Engineer McLean, VA: $193,400 - $220,700 for Lead Machine Learning Engineer Richmond, VA: $175,800 - $200,700 for Lead Machine Learning Engineer New York, NY: $211,000 - $240,800 for Lead Machine Learning Engineer Anytown, IL: $175,800 - $200,700 for Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Senior Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you'll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation). Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming languages like Python, Scala, or Java. Basic Qualifications: Bachelor's degree At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 3 years of experience building, scaling, and optimizing ML systems At least 2 years of experience leading teams developing ML solutions Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing performant, resilient, and maintainable code 3+ years of experience with data gathering and preparation for ML models 3+ years of people management experience ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents 3+ years of experience building production-ready data pipelines that feed ML models Ability to communicate complex technical concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $225,400 - $257,200 for Sr. Lead Machine Learning Engineer New York, NY: $245,900 - $280,600 for Sr. Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. 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