128 jobs found

Job Description Job Description Yardi Systems Specialist POSITION SUMMARY The Yardi Systems Specialist is a subject matter expert and administrator on the team for the Yardi Property Management system. This individual is accountable for the operational integrity, user support and continuous enhancement of the Yardi platform, the modules implemented to date, and those that are on the implementation roadmap. Particular emphasis on identifying and resolving data discrepancies arising from system integrations is an integral part of this role. The role bridges systems accuracy across Pratum's disciplines, including accounting aspects, with technical troubleshooting and process optimization, serving as both a hands-on problem solver and strategic system guide. This is not a remote role and will require on-site daily office presence in our company's Gaithersburg, MD HQ as a standard expectation.PRIMARY/ESSENTIAL DUTIES AND RESPONSIBILITIES Support and Administration Provide technical support to users of the Yardi products including Voyager Affordable, RentCafe, Procure to Pay and others in a timely manner. Create and maintain users, manage permissions and property assignments, scheduled reports, custom menus and workflows. Serve as the first point of contact for clients experiencing Yardi software-related problems, guiding them through problem identification, resolution, and prevention. Serve as the escalation point and liaison for Yardi support; collaborate with other team members and Yardi client support to resolve complex technical issues promptly. Track and review performance data of various Yardi modules to identify trends and issues and develop improvement plans. Work with vendors to establish and maintain Yardi data exchange. Yardi Migration and Implementation Serve as primary point of contact and technical project lead to migrate properties to Yardi platform. Assist with the onboarding of new properties and associated setup as part of the transition team, as well as the offboarding/transition of properties as the circumstances arise. Work with departments to test and implement new Yardi modules. Practice sound project management skills to ensure projects stay on track and implementation milestone objectives are met. Training Participates in, and serves as a facilitator and subject matter expert, in ensuring all system users are trained and capable of performing required job tasks within the Yardi system. This includes new hire and onboarding training, support for staff at new-hire orientation, development of training guides and curriculum/course materials, training of current staff who are or will be users of the system, etc. Analyze support tickets and work with department heads to create opportunities for additional training and continuous education. Identify and streamline processes and work with other departments to implement. Maintain system documentation, including configuration records, process workflows. REQUIRED MINIMUM QUALIFICATIONS Over 3 years' experience as a Yardi user and administrator including Voyager Affordable, RentCafe, Procure to Pay, and other system applications/features. Prior experience with other residential multi-family property management systems (e.g. RealPage/OneSite) is helpful. Experience in serving as a subject matter expert with the Yardi system, with demonstrated capability in handling/managing/resolving software system access, new property set-up, new user set-up and permissions, ad-hoc and scheduled report generation, custom menus, workflow creation, etc. Prior experience in-house with a multi-family property management company, including affordable housing (LIHTC, HUD Project Based Section 8, etc.). Prior experience in leading a software implementation effort from beginning to successful completion. Yardi software implementation experience strongly preferred. Capable of rallying positive support for achieving project milestones, managing and collaborating with stakeholders, both inside and outside of the company, to stay on-track and on-schedule with tact and professionalism. Capable of training employees in all operational aspects of Yardi. Comfortable presenting the subject matter one-on-one, to small groups in-person in a classroom setting, on-line via virtual/web-based training, etc. Excellent English verbal and written communication skills. Strong organizational and time management skills with excellent attention to detail. Adept at owning projects and tasks, managing deliverables to meet deadlines, connecting with people and facilitating effective collaboration to achieve successful outcomes. Strong project management skills. Advanced Microsoft Office Suite experience (Teams, Word, Excel, Outlook, PowerPoint, etc.) WORK ENVIRONMENT The role will be based at the company's corporate offices in Gaithersburg, MD and the work environment is predominantly office/clerical. This is not a remote role and will require on-site daily office presence as a standard expectation. While performing the duties of this job, the employee is regularly required to read, write, talk and hear. The employee frequently is required to sit; use hands/fingers to handle or feel (e.g. type); and reach with hands and arms. The employee is occasionally required to stand; walk; climb or balance; stoop, kneel, crouch, or crawl. The employee must occasionally lift and/or move up to 20+ pounds. Specific vision abilities required by this job include close vision, distance vision, depth perception, and ability to adjust focus. Must have reliable transportation and ability to meet attendance/punctuality requirements and to facilitate on-site visits to properties (5-10% travel estimated). This role is exempt and has an anticipated annualized base salary range of $65k-$75k for a new employee depending on a number of relevant factors including individuals' experience, qualifications, knowledge, skills, abilities, client/property or company budgetary limitations/guidelines, and other job-related company and market considerations. This position may be eligible to receive discretionary and/or performance-based bonuses on a spot or annual basis, which are variable depending on individual merit/performance, budgetary limitations, company performance, and other job-related factors. Full-time positions (30+ hours/week) are eligible for 2 weeks paid vacation, 1 week sick and related leave, 11 paid holidays, and health & welfare benefits as outlined on the Company's website. To learn more about our company and our benefits, go to: Pratum Companies is committed to a diverse workforce and is an Equal Opportunity Employer. Powered by JazzHR hSNOJCYi19

Job Description Job Description Senior Physical Electronic Security Technician - Data Centers Location: North Carolina Department: Physical Security / Critical Infrastructure Employment Type: Full-Time Position Summary We are seeking an experienced Senior Physical Electronic Security Technician with extensive expertise in enterprise electronic security systems, specifically the LenelS2 OnGuard platform, to install and commision critical security infrastructure within new construction data center environments. The ideal candidate will possess deep technical knowledge of integrated access control, IP video surveillance, intrusion detection, intercom systems, and security networking. This individual will lead installation, commissioning, troubleshooting, preventative maintenance, and lifecycle upgrades while ensuring the highest standards of security, reliability, and compliance expected within hyperscale and enterprise data centers. This role requires a technician who can work independently, lead field activities, mentor junior technicians, and interact professionally with customers, vendors, project managers, and security operations teams. Key Responsibilities Electronic Security Systems Install, commission, troubleshoot, and maintain enterprise electronic security systems. Perform basic programming, configuration, and diagnostics of Lenel OnGuard access control systems. Configure and maintain: Intelligent Controllers Access panels Card readers Electric locking hardware Request-to-exit devices Door position switches Elevator control integrations Maintain enterprise IP video surveillance platforms and associated hardware. Configure camera networks, recording servers, storage systems, and video analytics. Diagnose hardware, firmware, software, and communication failures. Data Center Security Infrastructure Support physical security systems protecting mission-critical data center facilities. Maintain strict compliance with customer security standards and change management processes. Work within highly controlled production environments with zero-tolerance for unnecessary downtime. Perform maintenance activities while minimizing operational impact. Understand redundancy requirements for: Controllers Network infrastructure Power systems Security servers Support security upgrades during maintenance windows. Systems Integration Integrate security platforms with: Video Management Systems (VMS) Intrusion Detection Systems (IDS) Visitor Management Systems Building Management Systems (BMS) Fire Alarm Interfaces Configure TCP/IP communications between enterprise security devices. Troubleshoot network communication issues involving switches, VLANs, PoE, and fiber infrastructure. Installation & Commissioning Lead field installation activities for new security deployments. Read and interpret: Construction drawings Security risers Wiring diagrams Floor plans Sequence of operations Install and terminate: Cat6 Fiber optic cabling Composite security cable RS-485 communications Low-voltage power circuits Perform commissioning, acceptance testing, and system turnover. Maintenance & Service Perform preventative maintenance inspections. Respond to emergency service calls. Diagnose complex system failures. Replace defective hardware. Perform firmware and software upgrades. Document repairs and maintain accurate service records. Leadership Mentor junior technicians. Lead small installation and service teams. Coordinate with project managers and security operations personnel. Provide technical guidance during complex troubleshooting activities. Ensure installations meet company quality standards and applicable codes. Required Qualifications 5+ years of experience installing and servicing enterprise electronic security systems. 3+ years of experience with Lenel OnGuard . Extensive experience supporting security systems in mission-critical data center environments. Strong understanding of: Access Control IP Video Surveillance Intrusion Detection Security Networking Low Voltage Systems Experience with enterprise security server architecture. Strong knowledge of: TCP/IP networking VLANs PoE Fiber optics Windows Server environments SQL fundamentals Ability to independently diagnose complex hardware and software issues. Experience working under formal change control procedures. Ability to read electrical and low-voltage construction drawings. Excellent customer communication and documentation skills. Preferred Qualifications Current LenelS2 OnGuard Certification (Associate, Professional, or Expert) Experience with: Genetec Security Center Milestone XProtect Avigilon Control Center Honeywell Pro-Watch Software House C•CURE 9000 Experience with intelligent locking hardware from manufacturers such as: ASSA ABLOY Allegion Knowledge of data center operational standards. OSHA 10 or OSHA 30 certification. Manufacturer certifications for enterprise access control or VMS platforms. Experience working in hyperscale cloud data centers. Technical Skills Enterprise Access Control Lenel OnGuard Administration Intelligent Controllers IP Camera Systems Video Management Systems Fiber Optic Installation Low Voltage Cabling Door Hardware Integration Network Troubleshooting TCP/IP SQL Databases Windows Server Power Supplies UPS Systems Security Networking System Commissioning Preventative Maintenance Root Cause Analysis Physical Requirements Lift up to 50 pounds. Work from ladders and lifts. Travel between customer sites as required. Work in active construction and mission-critical operational environments. Ability to participate in after-hours maintenance windows and on-call rotations. What Success Looks Like The successful candidate consistently delivers reliable, high-quality electronic security solutions with minimal disruption to critical operations. They serve as the technical expert for Lenel OnGuard systems, proactively resolve complex issues, ensure compliance with data center security standards, and provide leadership that enhances team performance and customer confidence. Company Description At Justified Technology, we believe our people are our greatest strength. We foster a collaborative, supportive culture where every team member is valued, respected, and empowered to succeed. From leadership to the field, we encourage open communication, continuous learning, and teamwork, ensuring employees have the resources and support they need to grow professionally. We are committed to creating an inclusive workplace built on equality, where diverse perspectives are welcomed, opportunities are earned through merit, and everyone is treated with fairness and respect. Our culture is centered on integrity, accountability, and helping one another succeed-making Justified Technology a place where careers thrive and people enjoy coming to work. Company Description At Justified Technology, we believe our people are our greatest strength. We foster a collaborative, supportive culture where every team member is valued, respected, and empowered to succeed. From leadership to the field, we encourage open communication, continuous learning, and teamwork, ensuring employees have the resources and support they need to grow professionally. We are committed to creating an inclusive workplace built on equality, where diverse perspectives are welcomed, opportunities are earned through merit, and everyone is treated with fairness and respect. Our culture is centered on integrity, accountability, and helping one another succeed-making Justified Technology a place where careers thrive and people enjoy coming to work.

Job Description Job Description Senior Physical Electronic Security Technician - Commercial Enterprise Systems Location: Colorado Department: Physical Security / Commercial Systems Employment Type: Full-Time Position Summary We are seeking an experienced Senior Physical Electronic Security Technician with extensive expertise in enterprise electronic security systems, specifically the e nterprise access control platforms, to install, service, and maintain commercial electronic security systems across a wide range of enterprise environments. The ideal candidate will possess deep technical knowledge of integrated access control, IP video surveillance, intrusion detection, intercom systems, and security networking. This individual will lead installation, commissioning, troubleshooting, preventative maintenance, and system upgrades while ensuring the highest standards of quality, reliability, and customer satisfaction. This role requires a technician who can work independently, lead field activities, mentor junior technicians, and interact professionally with customers, project managers, vendors, and internal operations teams. Key Responsibilities Electronic Security Systems Install, commission, troubleshoot, and maintain enterprise electronic security systems. Perform advanced programming, configuration, and diagnostics of access control systems. Configure and maintain: Intelligent controllers Access control panels Card readers Electric locking hardware Request-to-exit devices Door position switches Elevator control integrations Install and support enterprise IP video surveillance platforms and associated hardware. Configure cameras, recording servers, video storage, and analytics. Diagnose hardware, firmware, software, and communication failures. Commercial Enterprise Security Infrastructure Install and service integrated electronic security systems for commercial office buildings, healthcare facilities, educational campuses, manufacturing facilities, municipal buildings, and other enterprise environments. Coordinate system upgrades, expansions, and service activities with customers while minimizing disruption to daily operations. Perform system commissioning and acceptance testing for new construction and retrofit projects. Ensure installations comply with customer specifications, manufacturer requirements, and industry best practices. Support service calls, preventative maintenance programs, and emergency repair requests. Systems Integration Integrate security platforms with: Video Management Systems (VMS) Intrusion Detection Systems (IDS) Visitor Management Systems Building Automation Systems (BAS) Fire Alarm Interfaces Intercom and Communications Systems Configure TCP/IP communications between enterprise security devices. Troubleshoot network communication issues involving switches, VLANs, PoE infrastructure, and fiber optic networks. Installation & Commissioning Lead field installation activities for new security system deployments. Read and interpret: Construction drawings Security riser diagrams Wiring diagrams Floor plans Sequences of operation Install and terminate: Category cable Fiber optic cable Composite security cable RS-485 communications Low-voltage power circuits Perform commissioning, customer acceptance testing, training, and project turnover. Maintenance & Service Perform preventative maintenance inspections. Respond to scheduled and emergency service calls. Diagnose complex hardware and software failures. Replace defective equipment and perform firmware and software upgrades. Complete service reports and maintain accurate documentation of all work performed. Leadership Mentor junior technicians. Lead installation and service teams on commercial projects. Coordinate with project managers, general contractors, customer representatives, and subcontractors. Provide technical guidance during complex installations and troubleshooting activities. Ensure installations meet company quality standards, manufacturer specifications, and applicable electrical and life safety codes. Required Qualifications 5+ years of experience installing and servicing enterprise electronic security systems. 3+ years of advanced experience with Lenel OnGuard, CCure, Genetec, or ProWatch Systems . Extensive experience with commercial enterprise security systems including access control, video surveillance, intrusion detection, and integrated security platforms. Strong understanding of: Access Control IP Video Surveillance Intrusion Detection Security Networking Low Voltage Systems Experience with enterprise security server architecture. Strong knowledge of: TCP/IP networking VLANs Power over Ethernet (PoE) Fiber optics Windows Server environments SQL fundamentals Ability to independently diagnose complex hardware and software issues. Ability to read electrical and low-voltage construction drawings. Excellent customer communication, organization, and documentation skills. Preferred Qualifications Experience with: Genetec Security Center Milestone XProtect Avigilon Control Center Honeywell Pro-Watch Software House C•CURE 9000 Experience integrating intelligent locking hardware from manufacturers such as: ASSA ABLOY Allegion OSHA 10 or OSHA 30 certification. Manufacturer certifications for enterprise access control, video management, or intrusion detection platforms. Experience managing customer-facing service projects and leading installation teams. Technical Skills Enterprise Access Control Lenel OnGuard Administration Intelligent Controllers IP Camera Systems Video Management Systems Intrusion Detection Systems Intercom Systems Fiber Optic Installation Low Voltage Cabling Door Hardware Integration Network Troubleshooting TCP/IP SQL Databases Windows Server Power Supplies Security Networking System Commissioning Preventative Maintenance Root Cause Analysis Physical Requirements Lift up to 50 pounds. Work from ladders and lifts. Travel between customer sites as required. Work in occupied commercial buildings, construction sites, and secure facilities. Ability to participate in after-hours service calls, project cutovers, and occasional on-call rotations. What Success Looks Like The successful candidate consistently delivers reliable, high-quality electronic security solutions that exceed customer expectations. They serve as a technical expert for enterprise security systems, proactively resolve complex issues, ensure projects are completed safely and efficiently, and provide leadership that enhances team performance and customer confidence. Through technical excellence, professionalism, and a commitment to quality, they help reinforce Justified Technology's reputation as a trusted provider of integrated commercial security solutions. Company Description At Justified Technology, we believe our people are our greatest strength. We foster a collaborative, supportive culture where every team member is valued, respected, and empowered to succeed. From leadership to the field, we encourage open communication, continuous learning, and teamwork, ensuring employees have the resources and support they need to grow professionally. We are committed to creating an inclusive workplace built on equality, where diverse perspectives are welcomed, opportunities are earned through merit, and everyone is treated with fairness and respect. Our culture is centered on integrity, accountability, and helping one another succeed-making Justified Technology a place where careers thrive and people enjoy coming to work. Company Description At Justified Technology, we believe our people are our greatest strength. We foster a collaborative, supportive culture where every team member is valued, respected, and empowered to succeed. From leadership to the field, we encourage open communication, continuous learning, and teamwork, ensuring employees have the resources and support they need to grow professionally. We are committed to creating an inclusive workplace built on equality, where diverse perspectives are welcomed, opportunities are earned through merit, and everyone is treated with fairness and respect. Our culture is centered on integrity, accountability, and helping one another succeed-making Justified Technology a place where careers thrive and people enjoy coming to work.

Job Description Job Description Overview: We are seeking a Lead Systems Specialist to support the Pilot Bioproduction Facility (PBF) at the Walter Reed Army Institute of Research (WRAIR) in Silver Spring, Maryland. PBF is a one-of-a-kind cGMP-compliant pharmaceutical manufacturing facility engaging in next-generation development for cutting-edge companies and government agencies. The professionals at PBF are engaging in trailblazing endeavors every day. Most exciting, the end products vary, so every year brings multiple opportunities for professional enrichment in original projects. CAMRIS International, LLC, is a dynamic medical research and development firm that achieves innovative solutions to health and development challenges through high-quality, cost-effective programs and research management services. We combine our proven systems with today's most effective, evidence-based best practices. Our core practice areas include vaccine research, development, and production; microbiology and infectious disease research; biodefense; clinical research; global health security; and HIV/AIDS programs. Our employees enjoy a collegial environment where individual contributions matter at all levels. At CAMRIS, you will notably improve the lives of people at home and abroad. Responsibilities: Lead data integrity tasks including set up of testing workflows, configuring user access controls, integrating peripherals, setting automated schedules, managing alarms and general software administration tasks. Support cross-Functional teams acting as the main bridge between bench scientists, quality assurance (QA), and IT infrastructure teams. Collaborate with process engineers, scientists, operators, maintenance personnel, and vendors to identify opportunities for automation improvements and operational efficiencies. Communicate effectively, efficiently, and persistently with internal and external stakeholders including WRAIR Information Management Division, the PBF director and CAMRIS staff) Configure, maintain, troubleshoot, and optimize automation and control systems, including PLCs, machine to machine interfaces, and process data backups. Lead automation system design, implementation, commissioning, qualification, operation, and lifecycle management activities. Compliance & Validation: Ensuring data integrity, maintaining audit trails, and supporting GxP or regulatory standards (such as ISO/EPA guidelines). Assist WRAIR Information Management Division (IMD) and PBF end users with troubleshooting and upgrading applications supporting resolution of technical snags, data migrations, writing custom scripts or reports (e.g., LabVantage, Crystal Reports OSIsoft Pi), and managing data integrity through system upgrades. Coordinate with lab personnel to map out testing processes, perform market research, develop user requirement specifications (URS), and review associated software design specifications or functional specifications, as necessary. Develop and maintain system documentation including user requirements specifications (URS), functional specifications, control narratives, configuration details, password management, and backup protocols. Participate in commissioning, startup, and qualification activities including factory acceptance testing (FAT), site acceptance testing (SAT), installation qualification (IQ), operational qualification (OQ), and performance qualification (PQ). Establish software training for end users coordinating with operations, quality and quality assurance teams including authoring SOPs, creating training resources, and leading classroom training sessions at PBF. Lead the setup, configuration, and daily support of LabVantage modules at PBF. Ensure systems meet regulatory standards like GxP, 21 CFR Part 11, and data integrity (ALCOA+) principles. Support GMP manufacturing activities through adherence to quality systems, change management processes, deviation investigations, and corrective and preventive actions (CAPA). Design, implement and document the connections between the LIMS and lab equipment, chromatography data systems, and/or middleware. Compliance & Validation: Ensure systems meet regulatory standards like GxP, 21 CFR Part 11, and data integrity (ALCOA+) principles. Support engineering facilities, calibrations oversight, and shutdown execution at PBF as required. All other duties as required by the supervisor, manager, or program leadership. Qualifications: A Bachelor's degree in Engineering, Computer Science, Information Systems, Chemistry, Biology, or a related scientific/technical field. Understanding of GMP manufacturing practices and regulated computerized systems including data integrity and Good Automated Manufacturing Practice (GAMP) and ICH Q9 (Quality Risk Management). 5+ years working within R&D, MSAT or GMP environments supporting enterprise software or laboratory informatics, with firsthand LIMS administration and/or process automation experience. Experience with PLCs, DCS, SCADA, HMI systems, instrumentation, and industrial communication frameworks such as OPC-UA. Strong background in SQL, data analysis, and understanding of lab and clean core (manufacturing) workflows. Demonstrated oral and written communication with the ability to translate complex lab procedures into logical software requirements using flow-charts, presentations, and good engineering documentation. Experience managing subcontracted integration resources. Must be currently eligible to work in the United States without visa sponsorship and have lived in the United States for three of the past five years if a non-US citizen. A REAL ID or U.S. passport is required for WRAIR base access. Preferred Qualifications Familiarity with SQL databases, OSIsoft, and slocal application data stores associated with research, quality control, and manufacturing equipment. Data processing skills using R, python, Microsoft Excel, JMP and OSIsoft PI for quality control charting and multifactorial analysis. AKTA Unicorn method programing and configuration experience. Physical Requirements, Workplace Hazards and Conditions, and PPE and Chemical Requirements The physical requirements, workplace hazards and conditions, and PPE and chemical requirements described here are representative of those that a candidate must meet to perform the essential functions of this job. Reasonable accommodation may be provided to enable individuals with disabilities to perform essential job functions. Physical Demands Occasionally conduct sedentary work that primarily involves sitting/standing. Occasionally conduct light work that includes moving objects up to 20 pounds. Rarely conduct medium work that includes moving objects up to 50 pounds. Rarely conduct heavy work that includes moving objects up to 100 pounds. Rarely conduct very heavy work that includes moving objects over 100 pounds. Occasionally push or pull less than 25 pounds. Rarely push or pull 25 - 45 pounds. Rarely push or pull more than 45 pounds. Rarely reach above shoulder level. Constantly use both hands. Occasionally stand or walk for more than 25 minutes. Occasionally bend, reach, or twist repeatedly. Occasionally kneel, squat, or stoop. Rarely crawl or climb. Occasionally have clear vision (near and/or far), depth perception, peripheral vision, and/or visual acuity. Physical Activities Rarely ascend or descend ladders, stairs, scaffolding, ramps, poles, and the like. Rarely move self in different positions to accomplish tasks in various environments, including tight and confined spaces. Occasionally move about to accomplish tasks or move from one worksite to another. Constantly communicate with others to exchange information. Constantly assess the accuracy, neatness, and thoroughness of the work assigned. Environmental Conditions Occasionally work in low temperatures. Occasionally work in high temperatures. Rarely work in outdoor elements, such as precipitation and wind. Occasionally work in noisy environments. Rarely work in small and/or enclosed spaces. PPE and Chemical Requirements Occasionally wear PPE, including but not limited to gloves, face shields/goggles, safety glasses, and safety shoes. Occasionally wear a lab coat. Rarely wear earplugs/muffs. Occasionally work in a Clean Room Uniform. Occasionally wear a disposable dust/surgical mask. Rarely wear a respirator, such as a disposable respirator mask (N-95), half-face/full-face style, PAPR, SCUBA. Other: Sitting/standing should be managed. Extended screen time is expected. Please submit your resume online at . CAMRIS is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran status, disability status, or any other characteristic protected by any applicable federal, state, or local law. CAMRIS offers a comprehensive benefits package, including medical, dental, and vision insurance for individuals and families, FSAs, HSA, life and AD&D insurance, short- and long-term disability, legal services, voluntary hospital indemnity . click apply for full job details

Sr. Network Engineer (Azure focus) need for well-established California bank that has been in operation for over 100 years This Jobot Job is hosted by: Joseph Calabrese Are you a fit? Easy Apply now by clicking the "Quick Apply" button and sending us your resume. Salary: $150,000 - $185,000 per year A bit about us: A reputable and well-established California bank that has been in operation for over 100 years Why join us? Leverage the latest Network & Security technologies Strong benefits (M,D,V, and 401k) Profit sharing contribution - 10% Flexible work environment Extra paycheck at Christmas Job Details Requirements: Strong understanding of hybrid-cloud networking architectures, including hub-and-spoke, Virtual WAN, and cloud-to-datacenter connectivity solutions. Proven troubleshooting skills across routing, switching, firewalls, DNS, application connectivity, WAN services, and hybrid-cloud environments. Experience supporting universally available business-critical production environments with a focus on performance, reliability, disaster recovery, and operational excellence. Knowledge of network monitoring, telemetry, alerting, capacity planning, and performance management tools and methodologies. Experience with network automation, scripting, and Infrastructure-as-Code (IaC) technologies, including Terraform, Python, PowerShell, Ansible, APIs, and Git. Understanding of Zero Trust networking principles, cybersecurity best practices, threat prevention technologies, and regulatory compliance requirements. Strong technical documentation skills, including development of network diagrams, standards, configuration documentation, policies, and operational procedures. Excellent verbal and written communication skills with the ability to effectively collaborate across Infrastructure, Cloud, Information Security, Application Development, and business teams. Ability to manage multiple priorities, lead complex technical initiatives, and effectively support enterprise-wide infrastructure modernization efforts. Knowledge, Skills and Abilities Advanced hands-on experience with Fortinet and/or Palo Alto Networks Next-Generation Firewalls (NGFWs), including firewall policy administration, network segmentation, site-to-site and remote-access VPNs, threat prevention, and high-availability configurations. Strong expertise with Cisco and/or Arista enterprise, campus, and data center networking technologies, including routing, switching, network fabric, and infrastructure modernization initiatives. Experience designing, implementing, and supporting SD-WAN, SASE/SSE, and Azure Virtual WAN solutions to improve network performance, resiliency, security, and user connectivity. Demonstrated experience with Infrastructure as Code (IaC), network automation, and orchestration using Terraform, Python, PowerShell, Ansible, APIs, Git, or similar technologies. Experience administering and supporting enterprise load balancing, application delivery, DNS, DHCP, and IPAM platforms, including Infoblox, F5, or comparable solutions. Strong understanding of data center, colocation, carrier, and cloud connectivity services, including coordination with telecommunications providers, managed service vendors, and cloud partners. Experience supporting complex, universally available environments within banking, financial services, insurance, healthcare, or other regulated industries. Working knowledge of cybersecurity frameworks, regulatory requirements, and industry standards, including NIST, CIS Controls, FFIEC, PCI DSS, SOC 2, or equivalent governance frameworks. Exceptional problem-solving, analytical, and troubleshooting skills with the ability to diagnose and resolve complex network and cloud infrastructure issues. Ability to lead technical projects, manage competing priorities, and deliver solutions in a fast-paced, mission-critical environment. Strong interpersonal, collaboration, and relationship-building skills, with the ability to effectively partner with Information Security, Infrastructure, Cloud Engineering, Application Development, and business stakeholders. Excellent verbal, written, and presentation communication skills, including the ability to develop technical documentation, architecture diagrams, standards, and executive-level communications. Strong organizational skills with the ability to manage multiple initiatives, meet deadlines, and maintain a high level of accuracy and attention to detail. Ability to work independently while serving as a technical leader, mentor, and subject matter expert for network engineering and cloud networking technologies. Commitment to continuous learning and staying current with emerging networking, cloud, automation, and cybersecurity technologies and best practices. Education/Experience: Bachelor's degree in Information Technology, Computer Science, Engineering, or related field, or equivalent work experience. 7+ years of progressively responsible experience in enterprise network engineering and administration. Excellent analytical, troubleshooting, communication, and documentation skills. Relevant certifications preferred (CCNP, CCIE, Azure Network Engineer Associate, Azure Solutions Architect, or equivalent). Interested in hearing more? Easy Apply now by clicking the "Quick Apply" button. Jobot is an Equal Opportunity Employer. We provide an inclusive work environment that celebrates diversity and all qualified candidates receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, age (40 and over), disability, military status, genetic information or any other basis protected by applicable federal, state, or local laws. Jobot also prohibits harassment of applicants or employees based on any of these protected categories. It is Jobot's policy to comply with all applicable federal, state and local laws respecting consideration of unemployment status in making hiring decisions. Sometimes Jobot is required to perform background checks with your authorization. Jobot will consider qualified candidates with criminal histories in a manner consistent with any applicable federal, state, or local law regarding criminal backgrounds, including but not limited to the Los Angeles Fair Chance Initiative for Hiring and the San Francisco Fair Chance Ordinance. 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Sr. Azure Platform Engineer (IaC) need for well-established California bank that has been in operation for over 100 years This Jobot Job is hosted by: Joseph Calabrese Are you a fit? Easy Apply now by clicking the "Quick Apply" button and sending us your resume. Salary: $160,000 - $200,000 per year A bit about us: A reputable and well-established California bank that has been in operation for over 100 years Why join us? Leverage the latest Network & Security technologies Strong benefits (M,D,V, and 401k) Profit sharing contribution - 10% Flexible work environment Extra paycheck at Christmas Job Details The Senior Azure Cloud & Platform Engineer leverages deep expertise in Azure cloud services, Infrastructure as Code (IaC), Kubernetes, identity and access management, cybersecurity, automation, CI/CD pipelines, observability, and platform reliability engineering. Working closely with Infrastructure, Network Engineering, Information Security, Application Development, Enterprise Architecture, Risk Management, and Audit teams, this position helps design and deliver secure, compliant, and reusable cloud solutions that support the Bank's business objectives. Required Knowledge Strong experience designing, implementing, and supporting production Microsoft Azure environments, including enterprise-scale Azure Landing Zones and cloud governance frameworks. Demonstrated hands-on expertise with Terraform and Infrastructure as Code (IaC) principles, including the development and maintenance of reusable modules and automated deployment patterns. Experience designing, deploying, and supporting containerized platforms utilizing Azure Kubernetes Service (AKS), Kubernetes, Docker, Azure Container Registry (ACR), and related container technologies. Strong knowledge of Microsoft Entra ID, Azure Role-Based Access Control (RBAC), Managed Identities, Privileged Identity Management (PIM), Azure Policy, Key Vault, and Microsoft Defender for Cloud. Experience implementing and supporting CI/CD pipelines using Azure DevOps, GitHub Actions, Git, or comparable source control and automation platforms. Experience configuring and supporting enterprise monitoring, logging, and observability solutions utilizing Azure Monitor, Log Analytics, Application Insights, dashboards, and alerting tools. Proficiency in automation and scripting using PowerShell, Azure CLI, Python, Bash, or similar technologies to support provisioning, configuration management, and operational efficiency. Working knowledge of Azure networking services, including Virtual Networks (VNets), Subnets, Network Security Groups (NSGs), DNS, Private Endpoints, Load Balancers, Routing, ExpressRoute, VPN connectivity, and hybrid cloud architectures. Strong understanding of cloud security principles and frameworks, including Zero Trust, identity and access management, encryption, secrets management, vulnerability management, compliance controls, high availability, business continuity, and disaster recovery. Experience supporting regulated environments with an understanding of governance, risk management, audit requirements, and security best practices. Education and Experience Minimum of 7 years of experience in infrastructure engineering, platform engineering, DevOps, systems engineering, cloud engineering, or related technology disciplines. Minimum of 4 years of significant hands-on experience with Microsoft Azure, including the design, implementation, automation, and support of enterprise cloud environments. Experience working within a regulated industry, preferably banking, financial services, healthcare, insurance, or other environments with stringent compliance and security requirements. Working knowledge of industry security and compliance frameworks, including NIST, CIS Controls, FFIEC, PCI DSS, SOC 2, SOX, or similar regulatory and governance standards. Experience planning and executing migrations of VMware, virtualized infrastructure, and traditional data center workloads to Microsoft Azure. Experience implementing and supporting Azure services such as Azure Backup, Azure Site Recovery, Microsoft Sentinel, Azure SQL, Azure Storage, Azure Networking, and other Azure Platform-as-a-Service (PaaS) offerings. Understanding of FinOps principles, cloud financial management, cost optimization strategies, budgeting, forecasting, and resource utilization best practices. Demonstrated ability to design, implement, and support universally available, secure, and scalable cloud platforms in enterprise environments. Experience collaborating with Infrastructure, Security, Application Development, Architecture, Risk Management, Compliance, and Audit teams in support of cloud initiatives and operational excellence. Preferred Certifications: Microsoft Certified: Azure Administrator Associate Microsoft Certified: Azure Solutions Architect Expert Microsoft Certified: Azure DevOps Engineer Expert Microsoft Certified: Azure Security Engineer Associate Certified Kubernetes Administrator (CKA) Interested in hearing more? Easy Apply now by clicking the "Quick Apply" button. Jobot is an Equal Opportunity Employer. We provide an inclusive work environment that celebrates diversity and all qualified candidates receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, age (40 and over), disability, military status, genetic information or any other basis protected by applicable federal, state, or local laws. Jobot also prohibits harassment of applicants or employees based on any of these protected categories. It is Jobot's policy to comply with all applicable federal, state and local laws respecting consideration of unemployment status in making hiring decisions. Sometimes Jobot is required to perform background checks with your authorization. Jobot will consider qualified candidates with criminal histories in a manner consistent with any applicable federal, state, or local law regarding criminal backgrounds, including but not limited to the Los Angeles Fair Chance Initiative for Hiring and the San Francisco Fair Chance Ordinance. 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Up to $220K TS/SCI Mission Work in DC Own Postgres HA/DR, Performance & Security in a Mission-Critical Environment This Jobot Job is hosted by: Hunter King Are you a fit? Easy Apply now by clicking the "Quick Apply" button and sending us your resume. Salary: $180,000 - $220,000 per year A bit about us: We are an IT services firm delivering Enterprise Network Engineering, Enterprise IT, Program Management, and Project Management support to large commercial corporations, government agencies, and government contractors across the Washington, DC metropolitan area and beyond. We help our customers discover, evaluate, implement, and manage advanced technology projects, and we pride ourselves on a team that is detail-oriented, quick to adapt, and committed to the mission. We are seeking a Senior PostgreSQL Database Administrator to own the performance, availability, scalability, and security of PostgreSQL environments supporting a mission-critical government program. Why join us? Compensation up to $220K Health insurance Dental insurance Vision insurance Life insurance 401(k) with company match Paid time off Parental leave Mission-critical work supporting the national security community Job Details What We Are Looking For: We are seeking a Senior PostgreSQL Database Administrator with 10+ years of hands-on database administration experience, including at least 5 years of recent, deep expertise in PostgreSQL. This role is responsible for ensuring the performance, availability, scalability, and security of PostgreSQL database environments supporting a mission-critical government program. The ideal candidate can own core PostgreSQL responsibilities on day one, ramp quickly on program-specific tooling, and build strong customer trust through technical expertise and reliability. This role requires an active Top Secret clearance with SCI eligibility and is fully on-site in Washington, DC. What You Will Do: Design, implement, manage, and tune PostgreSQL databases in an enterprise environment. Own high availability and disaster recovery configurations for PostgreSQL environments. Perform database performance tuning, backups, replication, and recovery. Enforce database security controls, including encryption, key management, and compliance-aligned auditing. Enforce access controls, auditing, governance, and retention policies. Manage schemas, indexes, stored procedures, and permissions. Manage Kubernetes clusters and support containerized database and application operations. Administer CI/CD pipelines and automation supporting database and application delivery. Participate in Agile ceremonies and collaborative delivery activities. Support production operations with urgency and operational discipline. Communicate technical risks, issues, and recommendations clearly to stakeholders. What We Provide: Salaried, up to $220K DOE Full-Time Full Benefits Package Available, including 401(k) match What We Believe: We are committed to creating a diverse and inclusive environment and are proud to be an equal opportunity employer. We do not and will not discriminate in employment and personnel practices on the basis of race, sex, age, disability, religion, national origin, or any other basis prohibited by applicable law. Hiring, transferring, and promotion practices are performed without regard to the above listed items. What We Require: Active Top Secret clearance with current or previously held SCI access 10+ years of hands-on database administration experience 5+ years of recent experience as a DBA or database engineer with a primary focus on PostgreSQL Experience with PostgreSQL high availability, disaster recovery, replication, and performance tuning in enterprise environments Experience enforcing database security controls (encryption, key management, auditing) Experience with Kubernetes and CI/CD pipelines DoD 8140-compliant certification (e.g., Security+, GSEC, or higher) Bachelor's degree in Computer Science or related field preferred; relevant experience may substitute Ability to work on-site in Washington, DC Preferred: Master's degree Experience with SSIS, SSRS, and SSAS Familiarity with cloud platforms (Azure SQL, Amazon RDS) Microsoft Certified: Azure Database Administrator Associate or similar Interested in hearing more? Easy Apply now by clicking the "Quick Apply" button. Jobot is an Equal Opportunity Employer. We provide an inclusive work environment that celebrates diversity and all qualified candidates receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, age (40 and over), disability, military status, genetic information or any other basis protected by applicable federal, state, or local laws. Jobot also prohibits harassment of applicants or employees based on any of these protected categories. It is Jobot's policy to comply with all applicable federal, state and local laws respecting consideration of unemployment status in making hiring decisions. Sometimes Jobot is required to perform background checks with your authorization. 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Job Description Job Description Network Architect Gromelski and Associates, Inc. (GAI) partners with prime contractors to provide professional services. Key service areas include Engineering Design and Documentation; Software Development and Testing; System Integration, Testing and Evaluation; Lab Management and Field Installation; Integrated Logistics Support, Training Development and Delivery, Multimedia Support, and Technical System Support. Network Architect Job Description: Performs network design, development and troubleshooting, as well as system performance analysis and design. Network Architect Required Tasks: Evaluate utilizing dual Container Network Interface ( CNI) plugins to support multiple Maximum Transmission Unit ( MTU) sizes and assess the feasibility of using a single MTU within the PaaS environment versus dual MTUs for external workloads. The candidate should be familiar with multi MTU network messaging and Kubernetes CNI configurations. Because CNI is a pluggable framework, you can choose different networking solutions (Calico, Cilium, Flannel, etc.) that implement the CNI spec to meet your cluster's requirements. Familiarity with these network solutions is desired. Migrate to a 10.CCE for the PaaS network. Reduce number of Access Control Lists ( ACLs) for Control Plane traffic in Platform as a Service (PaaS) while maintaining subsystem subnet ingress/egress. Evaluate the need of applications using Broadcast on VxLAN. Perform network engineering in support of the Network Working Group (NWG IPT). Responsible for network monitoring and maintenance, configuration management, network support and problem resolution, system performance analysis and evaluation, performance metrics analysis, and failure analysis on the network for the program. Interfaces with customers, developers and support programs to ensure optimal flow of communications between subsystems. Design and enhancement and planning of computer network communications including specifications and schematics for network architecture on multiple subsystems. Perform evaluation and make recommendations on network hardware and software selections, implementation techniques, and tools for the most efficient solution to meet tactical programmatic needs, including present and future capacity requirements. Conduct performance and failover testing of network devices and their impact on system stability. Maintain technical expertise in all areas of network and computer hardware/software interconnection and interfaces - such as firewalls, routers, switches, gateways, middleware, etc. and OSI layer 1/2/3/4 functionality involved. Evaluate and recommend new technologies to enhance capabilities of the network system performance and monitoring. Perform network documentation for working group presentations and exchanges. Network Architect Required Skills: Experience with Kubernetes. Experience with Container Network Interfaces (CNI) technologies such as Calico, Cilium, Flannels, Canal, etc. Experience with ACLs is required. Network Integration experience for a variety of network protocol standards. Experience analyzing VLANs, spanning-tree, routing (static and dynamically implemented protocols), ACLs, IP addressing and subnetting. Knowledge of packet analysis tools such as Wireshark or Sniffers. Network Architect Desired Skills: Network development and integration experience for a variety of network protocol standards including TCP/IP, HSRP/VRRP, RIP, OSPF, BGP, RSTP (802.1w), MSTP (802.1s), DHCP, 802.1q tagging, multicast, PAgP or LACP (EtherChannel), QoS and Active-Active technologies (vPC and IRF) Strong network troubleshooting and problem identification Familiarity with network device vendors such as Cisco and Arista Familiarity with 1/10/25/40/100 Gig protocols, serial and satellite links, cable standards, and optical specifications/requirements. Familiarity with Linux OS, SNMP, Python and Bash is a plus Knowledge of TCP/UDP protocol packet format desirable Knowledge of Software Define Networking using OVS is a plus Knowledge of Kubernetes is a plus Knowledge of VxLAN is a plus Network Architect Additional Requirements: Bachelor's degree from an accredited college/university in a related discipline, or equivalent experience/combined education, with up to 3 years of professional experience. Strong communication skills. Must be able to obtain and keep a DoD Secret Clearance which means you must be a U.S Citizen. Travel: Minimal Job: Full-Time Employee, 40 hours/week Benefits: We offer a competitive benefit package. Click here Careers GAI () for more information. Job Location: Manassas, VA (Relocation Assistance Available) Start Date: Negotiable Salary Range: $135,000 - $200,000 Gromelski and Associates is an equal opportunity employer and does not discriminate in employment on the basis of race, color, religion, sex, pregnancy, national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service or other non-merit factor. Company Description Gromelski and Associates, Inc. is a small, woman-owned business. Since 1989, we have provided services for major corporations and large government agencies including the Social Security Administration, Lockheed Martin Corporation, Global Knowledge Network, Digital Equipment Corporation, Nextel Communications, Network Associates, Oracle Corporation, Department of Education, ExecuTrain Corporation, Federal Computer Corporation, and the U.S. Navy. Currently, we develop and deliver technical documentation and multimedia support including interactive electronic technical manuals (IETMs), multimedia applications, computer-based training (CBT), desktop simulation, technical system support including system engineering, software development and programming, lab management, system testing, integration, installation and maintenance for submarine combat systems. Company Description Gromelski and Associates, Inc. is a small, woman-owned business. Since 1989, we have provided services for major corporations and large government agencies including the Social Security Administration, Lockheed Martin Corporation, Global Knowledge Network, Digital Equipment Corporation, Nextel Communications, Network Associates, Oracle Corporation, Department of Education, ExecuTrain Corporation, Federal Computer Corporation, and the U.S. Navy. Currently, we develop and deliver technical documentation and multimedia support including interactive electronic technical manuals (IETMs), multimedia applications, computer-based training (CBT), desktop simulation, technical system support including system engineering, software development and programming, lab management, system testing, integration, installation and maintenance for submarine combat systems.

At Whitman, Requardt & Associates, LLP, we are People Focused and Project Driven. For more than 110 years, we have been known for quality work and quality employees. Join our team and help us design the infrastructure and buildings that improve the world. WRA is seeking a hands-on Information Systems Security Manager to support classified information systems, lead Risk Management Framework authorization and continuous monitoring activities, and help operate WRA's CMMC program and CUI enclave. The position is ideal for an ISSM or experienced ISSO ready to grow into broader program ownership. This is a broad, practical role supporting multiple specialized security environments within a large organization. The ISSM will work across security documentation, compliance, technical analysis, and hands-on implementation. Routine user support is handled by cleared technical staff, but the ISSM must be able to perform ISSO and limited systems administration work when needed. Success requires initiative, curiosity, sound judgment, attention to detail, and a willingness to work outside a narrowly defined lane. Responsibilities: Classified systems and RMF: Manage and support authorization, reauthorization, and continuous monitoring for government-sponsored classified systems and local facilities. Develop and maintain ATO packages and supporting artifacts, including System Security Plans, control implementation statements, assessment evidence, POA&Ms, agreements, test plans, and technical documentation. Perform control assessments, self-inspections, vulnerability management, recurring reporting, and security-impact reviews; coordinate changes and authorization matters with government security stakeholders. Maintain authorization information and evidence in eMASS or sponsor-specific systems. Prior eMASS experience is helpful but not required. CMMC and CUI enclave: Help lead WRA's CMMC program and CUI enclave, including NIST SP 800-171 documentation, evidence, policies, POA&Ms, access and change reviews, continuous monitoring, assessment preparation, and remediation tracking. Use IntelliGRC to maintain CMMC documentation and evidence, and coordinate shared responsibilities and deliverables with WRA's managed service provider (MSP) and external consultants. Prior IntelliGRC experience is not required. Hands-on security: Review logs, configure controls such as multifactor authentication, use vulnerability and compliance scanning tools, apply and remediate SRGs and STIGs, investigate findings, and validate corrective actions. Perform ISSO or limited systems administration duties for specific programs and serve as backup to cleared technical staff when needed. This is not primarily a help desk position. Support incident response, required reporting, policy and training activities, and clear communication of authorization status, vulnerabilities, risks, and remediation. Research unfamiliar requirements and technologies, develop practical recommendations, and perform other related security and IT duties in a small, collaborative environment. Requirements: Must be a US Citizen with Active DoD Top Secret/SCI clearance. Security+ or another applicable cybersecurity certification. Associate degree with at least seven years, bachelor's degree with at least three years, or an equivalent combination of education and relevant experience in information technology, cybersecurity, information assurance, or classified systems. Practical experience supporting RMF authorization and continuous monitoring, including substantive contributions to an ATO package, control documentation, assessment evidence, or vulnerability remediation. Working knowledge of NIST SP 800-53, RMF, security controls, POA&Ms, and the requirements to obtain and maintain an ATO. Hands-on ability with Windows systems, identity and access management, networks, logging, vulnerability scanning, security baselines, and troubleshooting. Strong technical writing and communication skills, with the ability to work independently, manage competing priorities, collaborate with technical and nontechnical stakeholders, and seek assistance when appropriate. Preferred Qualifications: Experience serving as an ISSM. WRA will also consider experienced ISSOs who have contributed substantially to authorization and continuous monitoring activities and are ready to assume broader responsibility. Experience taking a system through authorization, reauthorization, or a significant continuous monitoring cycle. Final ownership of a complete ATO package is preferred but not required. Familiarity with eMASS, ICD 503, SAP or SAR environments, or sponsor-specific authorization processes. Knowledge of CMMC, NIST SP 800-171, DFARS cybersecurity requirements, IntelliGRC or another GRC platform, and common security tools for vulnerability scanning, logging, endpoint protection, or configuration compliance. CISSP, CISM, or another advanced security certification. Benefits: WRA recognizes that employees play an important role in its success. Our commitment to full-time employees is reflected in the comprehensive benefits package we offer: Flexible work schedule options Competitive salary Leave accrual and paid holidays Healthcare benefits Group Life Insurance, as well as additional optional life Insurance, short and long term disability insurance Flexible spending accounts for medical and dependent care reimbursement 401(k) Retirement Plan Tuition Reimbursement Employee Assistance Program Parental and maternity leave benefits WRA is an equal opportunity/affirmative action employer and complies with all applicable anti-discrimination laws. The expected compensation range for this position is $110,000.00 - $165,000.00. This range represents a good faith estimate for this position. The specific compensation offered to a candidate may vary based on factors including, but not limited to, the candidate's relevant knowledge, training, skills, work location, and/or experience. Applicants must be currently authorized to work in the United States on a full-time basis without the need for employment-based visa sponsorship now or in the future. WRA will not sponsor applicants for U.S. work visa status for this opportunity. (no sponsorship is available for H-1B, L-1, TN, O-1, E-3, H-1B1, F-1, J-1, OPT, CPT or any other employment-based visa) Position # 3507 -Onsite - Mid-Level

Job Description Job Description We are seeking a Senior Network Security Engineer for an operations-first role supporting enterprise network security infrastructure across on-premises, remote-access, hybrid-cloud, and cloud-connected environments. This is not primarily an architecture/design role. The priority is a hands-on engineer who can administer, configure, maintain, troubleshoot, patch, upgrade, back up, validate, document, and operate production security platforms with minimal ramp-up. Firewall operations: hands-on Cisco and Palo Alto firewall administration, rule changes, NAT, troubleshooting, policy cleanup, upgrades, backups, logging, and production support. VPN / remote access: support for remote-access VPN, site-to-site VPN, user connectivity issues, certificates, authentication flows, and after-hours troubleshooting. RSA / MFA administration: RSA SecurID or equivalent MFA operations, token support, server administration, user troubleshooting, VPN integration, certificates, patching, backups, logs, and monitoring. Day-to-day operations: ticket resolution, monitoring alerts, health checks, change requests, incident support, maintenance windows, operational reporting, and customer support. Configuration and administration: installing, configuring, maintaining, patching, upgrading, backing up, validating, and troubleshooting assigned security platforms. Production troubleshooting: strong TCP/IP, DNS, routing, firewall logs, packet captures, VPN authentication, certificate, and connectivity troubleshooting. Documentation and process discipline: SOPs, runbooks, diagrams, change records, rollback plans, evidence collection, knowledge transfer, and formal change management. Federal/customer environment maturity: Public Trust eligibility, regulated-environment documentation, customer support, cross-team coordination, and comfort working with government stakeholders. The best candidate can credibly say: "I have operated enterprise Cisco and Palo Alto firewalls in production, handled firewall rule changes and troubleshooting, supported VPN users and site-to-site tunnels, administered or supported RSA/MFA tied to VPN access, followed formal change-management processes, maintained documentation and backups, and can step into daily operational support with minimal ramp-up." Scope and Role Boundaries Primary platforms include Cisco ASA/Firepower/FTD/FMC, Palo Alto NGFW/Panorama/GlobalProtect, remote-access and site-to-site VPN, RSA SecurID Authentication Manager or comparable MFA, monitoring/logging/SIEM integrations, and related network security controls. Coordinate with SOC/NOC, cloud, identity/directory, wireless/LAN, server, endpoint, system owner, application, governance, and vendor teams during changes, incidents, troubleshooting, compliance, and audit support. Cloudflare, Cisco ISE/NAC, secure web/email gateways, packet visibility tools, SD-WAN/SASE/ZTNA, AWS/Azure security, and F5/application-delivery awareness are useful where they intersect with assigned operational support, but the core need is firewall, VPN, RSA/MFA, and production operations. Key Responsibilities Provide daily, weekly, monthly, and annual operational support for assigned security systems, including tickets, alerts, health checks, email/phone support, metrics, status reporting, and operational validation. Administer and troubleshoot enterprise firewalls, including rule bases, NAT, segmentation, high availability, threat prevention, VPN integration, logging, secure baselines, rule reviews, recertification, cleanup, and decommissioning. Install, configure, maintain, patch, upgrade, back up, and validate firewall, VPN, MFA, and related network security systems in production environments. Support remote-access VPN, site-to-site VPN, partner connectivity, cloud connectivity, mobile/remote users, certificates, authentication policies, availability, utilization, and user access issues. Maintain and troubleshoot RSA SecurID Authentication Manager or equivalent MFA services, including servers/appliances, agents, certificates, HA, backups, logs, monitoring, directory integration, VPN authentication, and token lifecycle support. Respond to incidents, vulnerability notices, urgent requests, vendor advisories, PSIRT notices, system alerts, and emergency troubleshooting while minimizing service disruption. Use firewall logs, VPN logs, packet captures, SIEM data, monitoring tools, DNS/routing checks, and standard diagnostics to resolve complex connectivity, authentication, TLS/certificate, and application-flow issues. Create and maintain topology diagrams, equipment inventories, configurations, SOPs, runbooks, implementation plans, rollback plans, build/upgrade procedures, troubleshooting notes, and knowledge articles. Follow approved change, release, incident, problem, and configuration-management processes; prepare change records, peer-review materials, validation evidence, root-cause analysis, metrics, and audit artifacts. Support vulnerability remediation, POA&M tracking, continuous monitoring, compliance reviews, audit evidence collection, and coordination with ISSO, system owner, and security governance teams. Requirements 7+ years of experience in network security engineering, network infrastructure, cybersecurity infrastructure, or a closely related role. 5+ years of hands-on experience administering, maintaining, and troubleshooting enterprise firewall platforms in production environments. Hands-on experience with Cisco security technologies such as Cisco ASA, Firepower, FTD, FMC, AnyConnect/Secure Client, or equivalent Cisco firewall/VPN platforms. Hands-on experience with Palo Alto Networks technologies such as NGFW, Panorama, GlobalProtect, security profiles, App-ID/User-ID, logging, and policy optimization. Experience administering or supporting RSA SecurID Authentication Manager or comparable enterprise MFA/two-factor authentication platforms, including token support, server operations, patching/upgrades, backups, certificates, monitoring, and directory/VPN integration. Strong knowledge of firewall policy, NAT, VPNs, routing, DNS, DHCP, BGP, TLS/certificates, packet captures, log analysis, segmentation, high availability, and common network diagnostic tools. Experience with enterprise monitoring, logging, SIEM, alerting, vulnerability management, incident response, formal change management, and regulated-environment documentation. Ability to create clear technical documentation, support customers and stakeholders, prioritize operational work, communicate clearly, and coordinate across technical teams. Ability to obtain and maintain a Public Trust background investigation. Desired Certifications Relevant certifications are helpful but should not replace demonstrated hands-on experience. Examples include CCNP Security, CCIE Security, PCNSE, PCCSE, CISSP, CCSP, AWS Certified Security - Specialty, AWS Advanced Networking - Specialty, Microsoft Certified: Azure Security Engineer Associate, Microsoft Certified: Azure Network Engineer Associate, CompTIA Security+, CompTIA CySA+, GIAC certifications, or equivalent vendor/cloud certifications. Core Competencies Enterprise firewall engineering and policy lifecycle management VPN, remote access, RSA/MFA, and token lifecycle operations Cloudflare, edge security, secure access, and Zero Trust support Content filtering, secure web/email gateway, and NAC operations Hybrid-cloud network security and secure connectivity Monitoring, logging, SIEM integration, and incident response support Security visibility, packet analysis, and advanced troubleshooting Vulnerability remediation, compliance evidence, and POA&M support Change management, documentation, reporting, and operational metrics Technical leadership, customer support, and cross-team collaboration Benefits 401(k) 401(k) matching Dental insurance Flexible schedule Flexible spending account Health insurance Health savings account Life insurance Paid time off Professional development assistance Referral program Retirement plan Tuition reimbursement Vision insurance

Job Description Job Description Senior Physical Electronic Security Technician - Data Centers Location: Texas Department: Physical Security / Critical Infrastructure Employment Type: Full-Time Position Summary We are seeking an experienced Senior Physical Electronic Security Technician with extensive expertise in enterprise electronic security systems, specifically the LenelS2 OnGuard platform, to install and commision critical security infrastructure within new construction data center environments. The ideal candidate will possess deep technical knowledge of integrated access control, IP video surveillance, intrusion detection, intercom systems, and security networking. This individual will lead installation, commissioning, troubleshooting, preventative maintenance, and lifecycle upgrades while ensuring the highest standards of security, reliability, and compliance expected within hyperscale and enterprise data centers. This role requires a technician who can work independently, lead field activities, mentor junior technicians, and interact professionally with customers, vendors, project managers, and security operations teams. Key Responsibilities Electronic Security Systems Install, commission, troubleshoot, and maintain enterprise electronic security systems. Perform basic programming, configuration, and diagnostics of Lenel OnGuard access control systems. Configure and maintain: Intelligent Controllers Access panels Card readers Electric locking hardware Request-to-exit devices Door position switches Elevator control integrations Maintain enterprise IP video surveillance platforms and associated hardware. Configure camera networks, recording servers, storage systems, and video analytics. Diagnose hardware, firmware, software, and communication failures. Data Center Security Infrastructure Support physical security systems protecting mission-critical data center facilities. Maintain strict compliance with customer security standards and change management processes. Work within highly controlled production environments with zero-tolerance for unnecessary downtime. Perform maintenance activities while minimizing operational impact. Understand redundancy requirements for: Controllers Network infrastructure Power systems Security servers Support security upgrades during maintenance windows. Systems Integration Integrate security platforms with: Video Management Systems (VMS) Intrusion Detection Systems (IDS) Visitor Management Systems Building Management Systems (BMS) Fire Alarm Interfaces Configure TCP/IP communications between enterprise security devices. Troubleshoot network communication issues involving switches, VLANs, PoE, and fiber infrastructure. Installation & Commissioning Lead field installation activities for new security deployments. Read and interpret: Construction drawings Security risers Wiring diagrams Floor plans Sequence of operations Install and terminate: Cat6 Fiber optic cabling Composite security cable RS-485 communications Low-voltage power circuits Perform commissioning, acceptance testing, and system turnover. Maintenance & Service Perform preventative maintenance inspections. Respond to emergency service calls. Diagnose complex system failures. Replace defective hardware. Perform firmware and software upgrades. Document repairs and maintain accurate service records. Leadership Mentor junior technicians. Lead small installation and service teams. Coordinate with project managers and security operations personnel. Provide technical guidance during complex troubleshooting activities. Ensure installations meet company quality standards and applicable codes. Required Qualifications 5+ years of experience installing and servicing enterprise electronic security systems. 3+ years of experience with Lenel OnGuard . Extensive experience supporting security systems in mission-critical data center environments. Strong understanding of: Access Control IP Video Surveillance Intrusion Detection Security Networking Low Voltage Systems Experience with enterprise security server architecture. Strong knowledge of: TCP/IP networking VLANs PoE Fiber optics Windows Server environments SQL fundamentals Ability to independently diagnose complex hardware and software issues. Experience working under formal change control procedures. Ability to read electrical and low-voltage construction drawings. Excellent customer communication and documentation skills. Preferred Qualifications Current LenelS2 OnGuard Certification (Associate, Professional, or Expert) Experience with: Genetec Security Center Milestone XProtect Avigilon Control Center Honeywell Pro-Watch Software House C•CURE 9000 Experience with intelligent locking hardware from manufacturers such as: ASSA ABLOY Allegion Knowledge of data center operational standards. OSHA 10 or OSHA 30 certification. Manufacturer certifications for enterprise access control or VMS platforms. Experience working in hyperscale cloud data centers. Technical Skills Enterprise Access Control Lenel OnGuard Administration Intelligent Controllers IP Camera Systems Video Management Systems Fiber Optic Installation Low Voltage Cabling Door Hardware Integration Network Troubleshooting TCP/IP SQL Databases Windows Server Power Supplies UPS Systems Security Networking System Commissioning Preventative Maintenance Root Cause Analysis Physical Requirements Lift up to 50 pounds. Work from ladders and lifts. Travel between customer sites as required. Work in active construction and mission-critical operational environments. Ability to participate in after-hours maintenance windows and on-call rotations. What Success Looks Like The successful candidate consistently delivers reliable, high-quality electronic security solutions with minimal disruption to critical operations. They serve as the technical expert for Lenel OnGuard systems, proactively resolve complex issues, ensure compliance with data center security standards, and provide leadership that enhances team performance and customer confidence. Company Description At Justified Technology, we believe our people are our greatest strength. We foster a collaborative, supportive culture where every team member is valued, respected, and empowered to succeed. From leadership to the field, we encourage open communication, continuous learning, and teamwork, ensuring employees have the resources and support they need to grow professionally. We are committed to creating an inclusive workplace built on equality, where diverse perspectives are welcomed, opportunities are earned through merit, and everyone is treated with fairness and respect. Our culture is centered on integrity, accountability, and helping one another succeed-making Justified Technology a place where careers thrive and people enjoy coming to work. Company Description At Justified Technology, we believe our people are our greatest strength. We foster a collaborative, supportive culture where every team member is valued, respected, and empowered to succeed. From leadership to the field, we encourage open communication, continuous learning, and teamwork, ensuring employees have the resources and support they need to grow professionally. We are committed to creating an inclusive workplace built on equality, where diverse perspectives are welcomed, opportunities are earned through merit, and everyone is treated with fairness and respect. Our culture is centered on integrity, accountability, and helping one another succeed-making Justified Technology a place where careers thrive and people enjoy coming to work.

Job Description Job Description Description: Data Center Technician 2 402 Job Title: Data Center Technician 2 Location: Boydton, VA Work Site Type: Onsite Schedule: Wednesday Saturday 7am 6pm Duration: 12 Months Of Contract About the Role Our team is currently seeking a Data Center Technician 2 (S2) to support server operations at customer Data Centers. The ideal candidate combines strong technical capability across hardware, IT, diagnostics, and cabling management with a highly analytical mindset, strong attention to detail, self-motivation, and a positive, results-driven approach. Data Center Technicians are expected to provide feedback, create documentation for technical and non-technical processes, and contribute to knowledge resources such as KB articles, SOPs, lessons learned, and operational playbooks. This role is both internal- and customer-facing, requiring the ability to lead tasks, support initiatives, and drive assigned work to completion. Key Responsibilities " Prepare, stage, set up, start up, and shut down Data Center hardware including racks, hard drives, and switches according to checklists, guides, standard protocols, and email instructions. " Assist and guide other technicians in completing challenging or complex tasks. " Perform diagnostics and troubleshooting using standard procedures, identify root causes quickly, and replace faulty components with minimal customer and business disruption. " Complete post-execution quality checks and verify that grounding, staging, labeling, and cabling are completed according to safety protocols, deployment standards, and planned Network Design Tasks. Page 2 of 3 AMD General " Decommission hardware for simple changes and refreshes, including memory upgrades and operating system rebuilds, following standard procedures with minimal guidance. " Communicate, report, and escalate incidents to appropriate AMD management in line with established procedures. " Participate in daily safety briefings, complete required safety training, and comply with safety procedures including equipment use, lifting, electrical hazard controls, and ladder or rolling stair use. " Contribute to a positive team environment by sharing information, participating in team meetings, asking questions, and staying informed on the status of related work. " Share relevant information proactively to support efficient workflow and reduce the impact of changes on others. " Complete assigned tickets efficiently and in alignment with KPI expectations by task type, while meeting or exceeding established SLAs with minimal guidance. " Demonstrate ownership, accountability, and pride in service quality, task completeness, user experience, and Data Center facility standards. " Learn the customer's business and maintain strong client focus to understand the impact of completed tickets and assigned tasks. Technical Requirements " Basic server hardware knowledge with a strong understanding of component and system-level failures. " Ability to assist with failure analysis on field issues. " Ability to assist in tracking server fleet health, investigating emerging failure trends, supporting problem management, and validating SLA performance. " Solid experience using IPMI for diagnostics. " Ability to administer software tools including diagnostics, testing, and firmware updates. " Beginner-level capability in real-time issue resolution during new deployments. " Beginner-level experience with Windows Server OS and WinPE OS administration. " Basic Linux PXE services knowledge is a plus. " Basic Linux and Windows scripting experience. " Network troubleshooting capability across Layer 1, Layer 2, and Layer 3. " Virtual machine setup and environment configuration experience. " Ability to work autonomously and within local or geographically dispersed teams. Page 3 of 3 AMD General Minimum Qualifications " 1 years of experience as a Data Center Technician or in a closely related technical support role. " Associate degree in Computer Science, Computer Engineering, Information Technology, or equivalent experience preferred. " CompTIA A certification or equivalent experience. " CompTIA Server certification or equivalent experience. " CCENT certification or equivalent experience. " Windows OS experience. " CCNA certification preferred. " MCP or MCSE certification preferred. " Scripting experience preferred, including PowerShell, Python, or Bash. Physical Requirements " Ability to lift to 35 pounds (approximately 16 kg) when necessary. " Ability to safely climb ladders when necessary. " Ability to correctly wear required personal protective equipment when necessary. " Ability to stand and walk throughout the facility for extended periods without loss or reduction of productivity. " Ability to use hands to handle, control, or feel objects, tools, or controls; make quick and precise adjustments to machine controls; bend or twist the body; and repeat movements for extended periods without loss or reduction of productivity.

Machine Learning Engineer 3 Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: 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 or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 3 years of experience programming with Python, Java, Golang, or C++ At least 2 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 3 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data At least 1 year of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 1+ years of experience optimizing ML algorithms, configurations, and infrastructure 1+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 1+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 1+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) Authored/co-authored a paper on a ML technique, model, or proof of concept 1+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any 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: $161,800 - $184,600 for Machine Learning Engineer 3 New York, NY: $176,500 - $201,400 for Machine Learning Engineer 3 Plano, TX: $147,100 - $167,900 for Machine Learning Engineer 3 Richmond, VA: $147,100 - $167,900 for Machine Learning Engineer 3 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).

Machine Learning Engineer 5 (Senior Manager, IC) In Risk Tech, we provide the foundation for Capital One to thrive in an uncertain world. Our engaged, empowered, and intelligent people produce outstanding products, working toward the common goal of transforming risk management with technology. We build data-driven tools that use machine learning to prevent risks & automatically detect issues before they impact our customers, our business, or our communities. In this role at Risk Tech, you will work with our GRC team and partners across the company to build and deploy proprietary solutions for Risk management that are powered by state-of-the-art AI technology. Our products, enhanced with the transformative power of AI, are central to our business and deliver tremendous customer value. Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: 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 Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale 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 or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or related field 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning 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: $229,900 - $262,400 for Machine Learning Engineer 5 Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5 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).

Machine Learning Engineer 4 - Machine Learning Foundations (MLX) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: 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 or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any 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: $179,400 - $204,700 for Machine Learning Engineer 4 McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Jose, CA: $215,200 - $245,600 for Machine Learning Engineer 4 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).

Machine Learning Engineer 4 - Machine Learning Experiences (MLX) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: 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 or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any 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: $179,400 - $204,700 for Machine Learning Engineer 4 Cambridge, MA: $197,300 - $225,100 for Machine Learning Engineer 4 McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Jose, CA: $215,200 - $245,600 for Machine Learning Engineer 4 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, Machine Learning Engineer (People Leader) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: 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 Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale 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 Serve as a force-multiplier for the team, balancing deep, hands-on technical contribution and innovation with mentoring and elevating the skills of peers and junior engineers Recruit, nurture, and retain top engineering talent Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, and mentoring other members of the engineering community Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems At least 1 year of people leadership experience Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience managing and leading an ML engineering team 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models 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. McLean, VA: $229,900 - $262,400 for Sr. Manager, Machine Learning Engineer New York, NY: $250,800 - $286,200 for Sr. Manager, Machine Learning Engineer Plano, TX: $209,000 - $238,500 for Sr. Manager, Machine Learning Engineer San Francisco, CA: $250,800 - $286,200 for Sr. Manager, 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).

Machine Learning Engineer 4 (Python, AWS, SQL, GenAI) (Enterprise Platforms Technology) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. Enterprise Platforms Technology (EPTech) comprises many of Capital One's most important enterprise platforms. We play an essential role in establishing practices for building technology solutions across the company, while also delivering capabilities that exemplify those practices. Team: The Marketing and Messaging team is responsible for delivering hyper-personalized messages and experiences that will delight the customer, attract prospects and drive increasing business value. The team builds scalable platforms that deliver omnichannel messages in owned and paid Adtech channels. What You'll Do: 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 or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any 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: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Plano, TX: $179,400 - $204,700 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Francisco, CA: $215,200 - $245,600 for Machine Learning Engineer 4 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).

Machine Learning Engineer 5 (Senior Manager, IC) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: 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 Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale 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 or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning 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. Cambridge, MA: $229,900 - $262,400 for Machine Learning Engineer 5 McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5 San Francisco, CA: $250,800 - $286,200 for Machine Learning Engineer 5 San Jose, CA: $250,800 - $286,200 for Machine Learning Engineer 5 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).