9 jobs found in Plano

Job Description Job Description Job Title: Microsoft Endpoint & Workspace ONE Specialist Duration: Full-Time Hire / Permanent Role Location: Reston, VA or Plano, TX. Work Mode: Hybrid Duties and Responsibilities Systemone is seeking a Microsoft Endpoint & Workspace ONE Specialist? to support a large-scale enterprise environment within a cloud first infrastructure. This role is responsible for managing and supporting endpoint devices, mobile platforms, and enterprise mobility solutions while ensuring compliance, security, and operational stability across the environment. The ideal candidate will have experience supporting Apple macOS devices, mobile device management (MDM) platforms such as Omnissa Workspace ONE and Microsoft Intune, and enterprise mobile technologies. Responsibilities include troubleshooting endpoint and mobile device issues, monitoring system performance and compliance, analyzing logs to identify and resolve incidents, and partnering with engineering, security, and compliance teams to maintain endpoint protection standards. The role also requires strong documentation practices, incident management capabilities, and the ability to support change management initiatives in a regulated financial services environment. Required Qualifications . Hands on experience with Omnissa Workspace ONE and/or Microsoft Intune Experience supporting and troubleshooting Apple macOS environments Mobile device management and support for iOS and Android devices Ability to monitor system performance, compliance status, and operational health Experience analyzing logs and collaborating with engineering teams to resolve incidents Understanding of endpoint security controls, policy enforcement, and compliance requirements Strong troubleshooting and root cause analysis skills Experience documenting incidents, resolutions, and operational procedures with attention to detail Familiarity with IT Service Management (ITSM) processes and change management practices Experience working in enterprise cloud environments, preferably AWS based organizations Knowledge of ServiceNow for incident, problem, and change management processes Strong written and verbal communication skills Required Skills Amazon Web Services Cloud Analytical Thinking Communication Detail-oriented Problem Solving ServiceNow Change Management Desired Skillset: ? Relevant certifications such as Microsoft Intune, Workspace ONE, AWS Cloud Practitioner, or ITIL are a plus Education: Bachelor's degree in computer science, Information Systems, or a related field.? Ref: Pittsburgh

Staff Machine Learning Engineer 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: Deliver ML models and software components that solve challenging business problems in the financial services industry, working in collaboration with the Product, Architecture, Engineering, and Data Science teams Drive the creation and evolution of ML models and software that enable state-of-the-art intelligent systems Lead large-scale ML initiatives with the customer in mind Leverage cloud-based architectures and technologies to deliver optimized ML models at scale Optimize data pipelines to feed ML models Use programming languages like Python, Scala, Java, and GoLang Leverage compute technologies such as Dask and RAPIDS Evangelize best practices in all aspects of the engineering and modeling lifecycles Help recruit, nurture, and retain top engineering talent 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 8 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 5 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 architecting and designing resilient, large-scale, production machine learning systems from data preparation, to model training, and inference. 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 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) 7+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. Ability to communicate complex technical concepts clearly to a variety of audiences Driving impacts in the ML industry through conference presentations, papers, blog posts, open source contributions or patents Experience developing high-performing ML engineers with an inspiring leadership style 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: $269,100 - $307,200 for Staff Machine Learning Engineer Plano, TX: $244,700 - $279,200 for Staff Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Senior Staff Machine Learning Engineer 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: Deliver ML models and software components that solve challenging business problems in the financial services industry, working in collaboration with the Product, Architecture, Engineering, and Data Science teams Drive the creation and evolution of ML models and software that enable state-of-the-art intelligent systems Lead large-scale ML initiatives with the customer in mind Leverage cloud-based architectures and technologies to deliver optimized ML models at scale Optimize data pipelines to feed ML models Use programming languages like Python, Scala, Java, and GoLang Leverage compute technologies such as Dask and RAPIDS Evangelize best practices in all aspects of the engineering and modeling lifecycles Help recruit, nurture, and retain top engineering talent 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 10 years of experience programming with Python, Java, Golang, or C++ At least 8 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 8 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 8 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 architecting and designing resilient, large-scale, production machine learning systems from data preparation, to model training, and inference. 7+ years of experience optimizing ML algorithms, configurations, and infrastructure 7+ 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) 9+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. Experience shaping long term cross-organizational machine learning strategy Ability to communicate complex technical concepts clearly to executive leadership Recognized leader in the ML industry through conference presentations, papers, blog posts, open source contributions or patents Experience developing high-performing ML engineers with an inspiring leadership style 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: $314,800 - $359,300 for Sr. Staff Machine Learning Engineer Plano, TX: $286,200 - $326,700 for Sr. Staff 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).

Job Description Job Description Top Skills: LMS Administration Inventory Management Instructional Design Essential Duties and Responsibilities Learning Management System Administration Administer, maintain, and optimize the Learning Management System (LMS). Manage user accounts, learning assignments, certifications, and learning paths. Maintain system integrity, troubleshoot issues, and coordinate vendor support. Support system upgrades, testing, and implementation of new functionality. Reporting and Analytics Develop recurring and ad hoc reports and executive dashboards. Monitor compliance, certifications, and learning effectiveness. Analyze data and provide recommendations to improve business performance. Learning Content Development Design and maintain eLearning, job aids, guides, assessments, and knowledge articles. Ensure learning content reflects current operational processes and adult learning principles. Business Communications Develop professional communications for frontline agents, supervisors, managers, and leadership. Prepare operational announcements, policy updates, training notifications, and change management communications. Responsible for ensuring timely, creative and accurate dissemination of contact center communications, multimedia content and information Create a variety of content for platforms, ensuring quality, accuracy and effective storytelling that aligns with applicable messaging Operational Support Partner with Operations, Quality, Workforce Management, HR, and Leadership to support strategic initiatives. Provide consultation and performance support across all levels of the contact center. Device Inventory Management Maintain accurate device inventory records. Perform monthly and annual inventory reconciliations. Coordinate equipment assignments, returns, audits, and lifecycle management. Minimum Qualifications Bachelor's degree in Instructional Design, Business, Communications, Education or a related field, or equivalent combination of education and experience. Three (3) to five (5) years of experience administering a Learning Management System. Three (3) to five (5) years of experience supporting a contact center environment. Advanced proficiency with Microsoft Office, particularly Excel and PowerPoint. Excellent written, verbal, organizational, analytical, and project management skills. Preferred Qualifications Experience with Absorb, Cornerstone, Docebo, LearnUpon, or similar LMS platforms. Experience using Articulate Storyline, Rise, Adobe Captivate, or comparable authoring tools. Knowledge of adult learning theory, instructional design, and change management. Experience supporting technical support or customer care organizations. Core Competencies Learning Management Systems Administration Business Communication Instructional Design and Content Development Reporting and Data Analytics Project Management Contact Center Operations Expertise Continuous Improvement Collaboration and Stakeholder Management Performance Expectations Maintain accurate LMS records and high system availability. Deliver timely executive reporting and actionable analytics. Publish clear, professional communications that support operational readiness. Complete monthly and annual device inventory reconciliations with high accuracy. Support operational initiatives that improve employee capability and customer experience

Machine Learning Engineer 5 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. McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5 Plano, TX: $209,000 - $238,500 for Machine Learning Engineer 5 Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5 San Francisco, 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).

Machine Learning Engineer 4 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/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. Plano, TX: $179,400 - $204,700 for Machine Learning Engineer 4 McLean, VA: $197,300 - $225,100 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).

Job Description Job Description About Valitana Valitana is a rapid growing FinTech startup providing cutting-edge SaaS solutions for institutional investors. Founded in 2017, our platforms have advanced financial analysis, trade flow, and portfolio management tools. Valitana provides robust, intuitive solutions allowing our clients to make informed decisions by improving their operational workflows. With over 500+ active users, our institutional clients include CLO investors, CLO managers, hedge funds, asset managers, insurance companies, family offices, and broker dealers. Valitana was Ranked in the "Best CLO Analytics Service", "Best Secondary CLO Platform", and "Best CLO Portfolio Management Service" in the Creditflux CLO Census for 2023. Position Overview Valitana is seeking a Senior Full-Stack Technical Lead (backend-focused) to help accelerate technology and business growth within a FinTech, client-facing environment. This role is suited for a hands-on senior engineer and technical leader with strong system-design instincts for data-intensive applications, who thrives in a fast-paced, collaborative setting and takes ownership of delivering reliable, scalable, and secure software solutions. The ideal candidate combines deep hands-on technical expertise with the ability to lead, mentor, and influence other developers, while maintaining a strong product- and client-oriented mindset. This individual will play a key role in shaping both the platform and the people building it. Responsibilities Contribute to data-intensive, client-facing FinTech applications with a focus on scalability, performance, security, and correctness. Own feature areas, services, and components end-to-end-from design and implementation through production support-while guiding other engineers through delivery. Own technical design and delivery for a defined domain or service area. Ensure delivery meets functional and non-functional requirements. Lead technical execution for client-facing initiatives, partnering closely with product, business, and client stakeholders to translate requirements into robust, maintainable solutions. Provide technical leadership and day-to-day guidance to engineers, including reviewing work, mentoring team members, and helping raise the technical bar. Lead and manage a small team of engineers, supporting career growth and skill development. Act as primary technical escalation point for the domain and team. Operate with a high degree of autonomy within agreed architectural boundaries while helping set technical direction, priorities, and execution plans within the broader engineering organization. Uphold and reinforce coding standards, API design, architectural principles, and engineering best practices, contributing to their ongoing evolution. Proactively identify technical risks, design trade-offs, and delivery challenges, collaborating with peers and leadership to drive resolution. Foster a culture of quality and accountability through thoughtful code reviews, documentation, knowledge sharing, and cross-team collaboration. Qualifications 8+ years of experience as a Full-Stack or Back-End Developer within the FinTech or broader technology space. Experience leading multi-quarter technical initiatives. Ability to balance business delivery with long-term platform improvements. Experience leading, mentoring, or managing engineers, including providing technical guidance, conducting code reviews, supporting career development, and influencing technical direction. Strong proficiency in server-side programming languages and technologies - C#/.Net, ASP.Net Core, Entity Framework, SQL, Python is a plus. Experience with web frameworks and technologies - Angular, Javascript, Typescript. Strong understanding of agile development methodologies, with experience operating in fast-paced, iterative environments. Proven ability to operate as a self-starter and technical leader, balancing hands-on execution with strategic thinking and team collaboration. Experience designing, building, or supporting cloud-based architectures; familiarity with cloud-hosted systems (e.g., AWS, Azure, GCP) is highly desirable. Bachelor's degree in Computer Science, Engineering, or a related technical field. Preferred: Experience or familiarity with financial products, particularly structured products. Experience leading or managing a team of 5-10 engineers, with 1-2 years of direct management experience is a plus. What We Offer The base salary range for this role is $170,000 to $210,000. Valitana offers a competitive compensation package which includes base salary and an annual performance bonus. Employees also receive a comprehensive benefits package that includes an employer matched retirement plan, healthcare with medical, dental, vision, telemedicine, and PTO. Employees in this role will work in the office Mondays through Wednesdays with the flexibility to work remotely Thursdays and Fridays. Assessment and Automated Screening Tools As part of this hiring process, you may be asked to complete a technical assessment administered through HackerRank, a third-party platform. By participating, advancing, or completing the assessment you are consenting to HackerRank possibly using automated features to evaluate or score the submitted work, and information about your submission is processed by that platform. Categories of data processed: The code or written work you submit, assessment scores, completion time, and, if enabled, session activity data. Source of that data is the information you provide directly by completing the assessment. How it is assessed: A Valitana employee reviews assessment results, and no hiring decision is made solely on the basis of an automated score. If you would like more information about how the assessment is evaluated contact Valitana Human Resources at . Equal Opportunity and Accommodation Valitana is an equal opportunity employer. We consider all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, ancestry, age, disability, pregnancy, veteran or military status, genetic information, or any other characteristic protected by federal or Connecticut law. If you need a reasonable accommodation to apply, interview, complete an assessment, or otherwise participate in this hiring process, contact the Human Resources team at . Requesting an accommodation will not affect how your application is considered. Powered by JazzHR UtEVAIiSzB

Job Description Job Description CoreWeave is The Essential Cloud for AI . Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at . About the role: The Tiger Team, Technical Deployment Lead, will support the expansion of our Data Centers across the U.S and Canada. The Technician must work well with others and will help ensure overall availability and reliability to meet or exceed the defined service levels of the hybrid travel data center operations. This position involves infrastructure delivery on all CoreWeave data centers, training on-site teams, and hardware and network diagnostics. This is a 100% on-site role at one of our Central region, U.S. data centers , with up to 60% of travel required on a rotational basis. What You'll Do: Nationwide travel to data centers to build and deploy new and ongoing sites Implementation and documentation of a global data center standard Troubleshoot hardware and networks Root cause analysis of hardware and software failures Train internal teams Perform on-site audits through our set QA/QC process Provide technical support to global data center teams Develop tools and scripts to update server and networking hardware Perform maintenance of test and tools equipment Follow-up project support Who You Are: You are a skilled and motivated technician with the ability to influence others who thrives in a fast-paced, hands-on environment. You are passionate about technology and possess the following qualifications: You have hands-on experience troubleshooting and assembling computer hardware. You are proficient with the Linux operating system. You possess a comprehensive knowledge of data center cut sheets and technical documentation. You have a strong understanding of best practices for cable management and hardware orientation. You are an effective communicator who collaborates seamlessly with network engineers and project managers. You excel at time management and take full ownership of your projects to meet demanding deadlines. You are flexible, with the ability to travel and work in a 24/7 operational environment. You can lift up to 50 lbs and are comfortable working in elevated locations. (All physical requirements are subject to reasonable accommodations.) Why CoreWeave? At CoreWeave, we work hard, have fun, and move fast! We're in an exciting stage of hyper-growth that you will not want to miss out on. We're not afraid of a little chaos, and we're constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values: Be Curious at Your Core Act Like an Owner Empower Employees Deliver Best-in-Class Client Experiences Achieve More Together We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and enables the development of innovative solutions to complex problems. As we get set for takeoff, the organization's growth opportunities are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us! The base salary range for this role is $90,000 to $102,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). What We Offer The range we've posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location. In addition to a competitive salary, we offer a variety of benefits to support your needs. The benefits below reflect our US-based offerings for full-time employees; for roles in other locations, benefits vary and are shared during the hiring process. These include: Medical, dental, and vision insurance - 100% paid for by CoreWeave Company-paid Life Insurance Voluntary supplemental life insurance Short and long-term disability insurance Flexible Spending Account Health Savings Account Tuition Reimbursement Ability to Participate in Employee Stock Purchase Program (ESPP) Mental Wellness Benefits through Spring Health Family-Forming support provided by Carrot Paid Parental Leave Flexible, full-service childcare support with Kinside 401(k) with a generous employer match Flexible PTO Catered lunch each day in our office and data center locations A casual work environment A work culture focused on innovative disruption California Applicants California Consumer Privacy Act Equal Opportunity & Accommodations CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information. As part of this commitment and consistent with the Americans with Disabilities Act (ADA) , CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: . Export Control Compliance This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. 1157, or (iv) asylee under 8 U.S.C. 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.

Job Description Job Description Digital Creative Specialist This Japanese company is a production and technology company that provides creative production, digital initiatives, technical content, and AI-enabled knowledge platforms for global OEM and enterprise clients. With a strong focus on the automotive and mobility sectors, we specialize in delivering high-quality creative and digital solutions that balance brand value with real-world operational needs. Role Summary This position is a working-level, hands-on role that operates under the direction and guidance of the company president, as well as the Creative Manager when needed. The Digital Creative & Event specialist is expected to mainly support the company president across two areas of equal importance: coordinating company events and providing digital creative support. On the event side, the role leads and supports event coordination and logistics-most often for events attended by international and visiting media-including on-site logistics, vendor coordination, guest engagement, and serving as a communication bridge between visiting executives from the client/headquarter and the internal team. On the creative side, the role plans, produces, and contributes to digital creative productions. The role also carries exposure to basic digital marketing operations. Key Responsibilities Creative Production Execute creative production tasks based on direction and strategy from the Creative Manager Manage content quality, revisions, and final deliverables Support coordination with external creative vendor Event Coordination & Support Lead and coordinate logistics for company events, including events attended by international and visiting media Plan and manage event preparation, including scheduling, venue and on-site setup, run-of-show, and day-of execution Source, brief, and manage external vendors (e.g., venue, catering, AV, production, and transportation), and serve as the primary point of contact before and during events Track event budgets, timelines, and deliverables to ensure events are organized, on schedule, and ready ahead of time Coordinate guest and media communications, including invitations, scheduling, on-site reception, and hospitality Engage with and host guests on-site, ensuring a professional, welcoming, and smoothly run experience Serve as a communication bridge between visiting executives from the client/headquarter and the internal team, ensuring expectations are clearly understood and met Anticipate and respond quickly to on-site needs and last-minute changes while maintaining a polished and mindful presence with guests and executives Support post-event wrap-up, including vendor follow-up, recap reporting, and lessons learned for future events Digital Marketing Support Provide support on digital marketing initiatives Preferred Qualification Photo / Video production experience Digital advertising or social media experience Global project experience Interest in automotive, mobility, or technology fields Experience supporting events with international media or VIP guests Background or experience in event planning, coordination, or hospitality Familiarity with event logistics, vendor management, and on-site coordination Comfort acting as a liaison across cultures and organizational levels Tools & Skills Adobe Creative Cloud - Google Analytics Digital advertising and social platforms - Project management tools Work Type Full-time Hybrid (Texas-base) Travel Approximately once per month Domestic and international travel may be required Work Authorization Candidates must be authorized to work in the United States. Visa sponsorship is not available.