Capital One
New York, New York
Machine Learning Engineer 4 - Finance Tech 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. Finance Tech is responsible for transforming Capital One's financial engine into the most trusted, nimble, and insightful in the industry. Our core mission is to engineer outcomes that strategically enable the Finance organization and the broader Enterprise to remain efficient. This mission is driven by four technical and functional pillars: Forecasting & Resiliency, providing advanced decision support; Treasury & Trade managing sophisticated cash and investment lifecycles; and Accounting & Reporting, ensuring the integrity of our general ledger and regulatory commitments. Powering these pillars are our Data and Core capabilities, which manage the orchestration, sourcing, and pipelines for critical financial data products. By defining the next generation of financial technology, we ensure that every business process is backed by high fidelity tracking and reporting. Together, we are not just supporting the bottom line - we are building a strategic enabler that operates as a world class financial engine. 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 This role is designated as a hybrid position. You are expected to adhere to Capital One's hybrid policy regarding required on-site presence at your designated office location. 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. 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 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 - Finance Tech 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. Finance Tech is responsible for transforming Capital One's financial engine into the most trusted, nimble, and insightful in the industry. Our core mission is to engineer outcomes that strategically enable the Finance organization and the broader Enterprise to remain efficient. This mission is driven by four technical and functional pillars: Forecasting & Resiliency, providing advanced decision support; Treasury & Trade managing sophisticated cash and investment lifecycles; and Accounting & Reporting, ensuring the integrity of our general ledger and regulatory commitments. Powering these pillars are our Data and Core capabilities, which manage the orchestration, sourcing, and pipelines for critical financial data products. By defining the next generation of financial technology, we ensure that every business process is backed by high fidelity tracking and reporting. Together, we are not just supporting the bottom line - we are building a strategic enabler that operates as a world class financial engine. 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 This role is designated as a hybrid position. You are expected to adhere to Capital One's hybrid policy regarding required on-site presence at your designated office location. 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. 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 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).
Capital One
Mc Lean, Virginia
Machine Learning Engineer 4 - Finance Tech 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. Finance Tech is responsible for transforming Capital One's financial engine into the most trusted, nimble, and insightful in the industry. Our core mission is to engineer outcomes that strategically enable the Finance organization and the broader Enterprise to remain efficient. This mission is driven by four technical and functional pillars: Forecasting & Resiliency, providing advanced decision support; Treasury & Trade managing sophisticated cash and investment lifecycles; and Accounting & Reporting, ensuring the integrity of our general ledger and regulatory commitments. Powering these pillars are our Data and Core capabilities, which manage the orchestration, sourcing, and pipelines for critical financial data products. By defining the next generation of financial technology, we ensure that every business process is backed by high fidelity tracking and reporting. Together, we are not just supporting the bottom line - we are building a strategic enabler that operates as a world class financial engine. 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 This role is designated as a hybrid position. You are expected to adhere to Capital One's hybrid policy regarding required on-site presence at your designated office location. 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. 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 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 - Finance Tech 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. Finance Tech is responsible for transforming Capital One's financial engine into the most trusted, nimble, and insightful in the industry. Our core mission is to engineer outcomes that strategically enable the Finance organization and the broader Enterprise to remain efficient. This mission is driven by four technical and functional pillars: Forecasting & Resiliency, providing advanced decision support; Treasury & Trade managing sophisticated cash and investment lifecycles; and Accounting & Reporting, ensuring the integrity of our general ledger and regulatory commitments. Powering these pillars are our Data and Core capabilities, which manage the orchestration, sourcing, and pipelines for critical financial data products. By defining the next generation of financial technology, we ensure that every business process is backed by high fidelity tracking and reporting. Together, we are not just supporting the bottom line - we are building a strategic enabler that operates as a world class financial engine. 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 This role is designated as a hybrid position. You are expected to adhere to Capital One's hybrid policy regarding required on-site presence at your designated office location. 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. 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 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).
Novalink Solutions LLC
Tallahassee, Florida
Job Description Job Description 4. Scope of Servies The Florida Department of Transportation, Office of Information Technology (OIT) - Integration Services is in search of a Senior Network Engineer to play a key role in assisting the Office of Information Technology in the establishment of new integration methods and standards, along with implementing system integrations, according to those established methods and standards. Duties and Responsibilities will include but are not limited to: 1. Perform security administration to configure and document firewall infrastructure access rules and work with peripheral network components in the technology environment with Palo Alto, Checkpoint and Global Protect VPNs. 2. Firewall deployments, rule migrations, firewall administration and converting existing rule based policies onto new platforms. 3. Works with critical core network infrastructure devices like Next Gen Firewall, VPNs, log collectors and monitors which play a crucial role in security for our IT environment. 4. Works with cloud network infrastructure to configure firewall, security policies and monitor network traffic. 5. Develop and maintain documentation following NIST guidelines. 6. Project Manager; 7. Data Administration; 5 Education Bachelor's Degree in Computer Science, Information Systems or other related field. Or equivalent work experience. Preferred Certifications (PCNSE, CISSP, CCNP, CCIE) 6. Experience 1. Typically have 5 to 10 years of combined IT and security work experience with a broad range of exposure to systems analysis, applications development, database design and administration 2. Three to five years of experience with information security tools based on NIST standards. 3. Requires knowledge of security issues, techniques, and implications across all existing computer platforms. Preference given for experience with NGFW Palo Alto or Checkpoint security products. 4. Experience using schematic diagramming tools to map infrastructure layouts. 7 Primary Job Duties/ Tasks Senior Network Engineer - Job Duties 1. Develops, implements, and manages enterprise security solutions across multiple IT functional areas, including network infrastructure, data, systems, cloud environments, telecommunications, and Web-based services. Designs and maintains secure network architectures, segmentation strategies, access controls, firewalls, VPNs, encryption technologies, and other security controls. 2. Develops, implements, and maintains enterprise security policies, standards, procedures, and technical controls governing user authentication, privileged access, network access, security monitoring, vulnerability management, firewall administration, encryption, remote access, and incident escalation. Ensures security practices align with organizational requirements, industry standards, and applicable regulatory requirements. 3. Performs security risk assessments and develops risk-based response strategies for enterprise network and infrastructure environments. Prepares executive-level status reports, risk assessments, security metrics, and recommendations addressing vulnerabilities, emerging threats, security incidents, and operational risks. 4. Monitors, analyzes, and responds to cybersecurity threats and security events, including malware, software vulnerabilities, unauthorized access attempts, network anomalies, and policy violations. Administers and monitors security profiles and access controls, reviews security alerts and violation reports, investigates security exceptions, and coordinates remediation activities. Maintains comprehensive documentation of security controls, configurations, incidents, and corrective actions. 5. Evaluates emerging network and security technologies, products, and procedures to improve infrastructure reliability, security, performance, and operational efficiency. Leads technical evaluations, proof-of-concept activities, product assessments, and implementation recommendations for enterprise networking and cybersecurity solutions. 6. Provides advanced technical support and consultation to business and IT stakeholders on complex network, infrastructure, and cybersecurity issues. Troubleshoots escalated network and security incidents, provides technical guidance to infrastructure teams, and educates IT and business personnel on security policies, secure configurations, access requirements, and risk mitigation practices. 7. Provides security expertise and technical leadership throughout the IT project lifecycle, including requirements development, architecture and design, implementation, testing, deployment, and operational support. Reviews project designs and proposed solutions to identify security risks and ensures appropriate security controls are incorporated into network, cloud, application, and infrastructure initiatives. 8. Designs, implements, and supports enterprise network infrastructure, including LAN/WAN, routing and switching, wireless networks, firewalls, VPNs, network segmentation, Internet connectivity, cloud connectivity, and data center infrastructure. Develops network solutions that support high availability, resiliency, scalability, and security requirements. 9. Leads the investigation and resolution of complex network and security incidents, utilizing network monitoring, logging, packet analysis, performance data, and security tools to identify root causes and implement corrective actions. Coordinates with vendors, technical teams, and organizational stakeholders during critical incidents and service disruptions. 10. Develops network security architecture and segmentation strategies designed to limit lateral movement, protect critical systems, isolate sensitive workloads, and establish appropriate security boundaries between users, applications, devices, and infrastructure. Evaluates east-west and north-south traffic flows to identify security risks and opportunities for improved network controls. 11. Establishes and monitors network performance and security metrics to identify trends, capacity requirements, vulnerabilities, and potential operational risks. Develops dashboards, key performance indicators, and management reports to support data-driven infrastructure and security decisions. 12. Maintains technical documentation and configuration standards for network and security infrastructure, including network diagrams, IP addressing, VLANs, firewall rules, access controls, security configurations, operational procedures, and disaster recovery requirements. Ensures documentation remains accurate and aligned with the current enterprise environment. 13. Collaborates with architecture, cybersecurity, systems, database, application, cloud, telecommunications, and infrastructure teams to develop integrated technology solutions. Serves as a senior technical resource and provides guidance on enterprise networking, security architecture, infrastructure design, and technology modernization. 14. Provides technical leadership and mentoring to network and security staff, establishes network engineering standards and best practices, reviews technical solutions, and assists with the development of team capabilities in enterprise networking, cybersecurity, cloud infrastructure, and emerging technologies. Senior-Level Requirements Must have extensive knowledge and demonstrated experience in enterprise networking, cybersecurity, systems, databases, cloud infrastructure, and/or Web operations. The senior-level Network Engineer is responsible for developing and implementing enterprise network and security strategies, leading complex technical projects, designing secure and resilient infrastructure, resolving the most complex network and security issues, conducting risk assessments, evaluating emerging technologies, and providing technical guidance to IT and business leadership. The position requires advanced knowledge of network architecture, routing and switching, firewalls, VPN technologies, network segmentation, wireless infrastructure, cloud networking, identity and access management, security monitoring, incident response, vulnerability management, disaster recovery, and enterprise security controls. 8 Job Specific Skills and Abilities (KSAs): Intermediate professional level role. Works independently or on multiple IT security projects as a project team member, occasionally as a project leader. Works on small to large, complex security issues or projects that require increased skill in multiple IT functional areas. May coach more junior staff. 9 General Knowledge Skills and Abilities (KSAs): The submitted candidate must be able to apply common knowledge, skills, and abilities in the following areas: 1. Communication: Have the ability to clearly convey information, in both written and verbal formats, to individuals or groups in a wide variety of settings (i.e.; project team meetings, management presentations, etc.). Must have the ability to effectively listen and process information provided by others. 2. Customer Service: Works well with clients and customers (i.e.; business office, public, or other agencies). Able to assess the needs of the customer, provide information or assistance to satisfy expectations or resolve a problem. 3. Decision Making: Makes sound, well-informed, and objective decisions. 4. Flexibility: Is open to change, new processes (or process improvement), and new information. Has the ability to adapt in response to new information, changing conditions . click apply for full job details
Job Description Job Description 4. Scope of Servies The Florida Department of Transportation, Office of Information Technology (OIT) - Integration Services is in search of a Senior Network Engineer to play a key role in assisting the Office of Information Technology in the establishment of new integration methods and standards, along with implementing system integrations, according to those established methods and standards. Duties and Responsibilities will include but are not limited to: 1. Perform security administration to configure and document firewall infrastructure access rules and work with peripheral network components in the technology environment with Palo Alto, Checkpoint and Global Protect VPNs. 2. Firewall deployments, rule migrations, firewall administration and converting existing rule based policies onto new platforms. 3. Works with critical core network infrastructure devices like Next Gen Firewall, VPNs, log collectors and monitors which play a crucial role in security for our IT environment. 4. Works with cloud network infrastructure to configure firewall, security policies and monitor network traffic. 5. Develop and maintain documentation following NIST guidelines. 6. Project Manager; 7. Data Administration; 5 Education Bachelor's Degree in Computer Science, Information Systems or other related field. Or equivalent work experience. Preferred Certifications (PCNSE, CISSP, CCNP, CCIE) 6. Experience 1. Typically have 5 to 10 years of combined IT and security work experience with a broad range of exposure to systems analysis, applications development, database design and administration 2. Three to five years of experience with information security tools based on NIST standards. 3. Requires knowledge of security issues, techniques, and implications across all existing computer platforms. Preference given for experience with NGFW Palo Alto or Checkpoint security products. 4. Experience using schematic diagramming tools to map infrastructure layouts. 7 Primary Job Duties/ Tasks Senior Network Engineer - Job Duties 1. Develops, implements, and manages enterprise security solutions across multiple IT functional areas, including network infrastructure, data, systems, cloud environments, telecommunications, and Web-based services. Designs and maintains secure network architectures, segmentation strategies, access controls, firewalls, VPNs, encryption technologies, and other security controls. 2. Develops, implements, and maintains enterprise security policies, standards, procedures, and technical controls governing user authentication, privileged access, network access, security monitoring, vulnerability management, firewall administration, encryption, remote access, and incident escalation. Ensures security practices align with organizational requirements, industry standards, and applicable regulatory requirements. 3. Performs security risk assessments and develops risk-based response strategies for enterprise network and infrastructure environments. Prepares executive-level status reports, risk assessments, security metrics, and recommendations addressing vulnerabilities, emerging threats, security incidents, and operational risks. 4. Monitors, analyzes, and responds to cybersecurity threats and security events, including malware, software vulnerabilities, unauthorized access attempts, network anomalies, and policy violations. Administers and monitors security profiles and access controls, reviews security alerts and violation reports, investigates security exceptions, and coordinates remediation activities. Maintains comprehensive documentation of security controls, configurations, incidents, and corrective actions. 5. Evaluates emerging network and security technologies, products, and procedures to improve infrastructure reliability, security, performance, and operational efficiency. Leads technical evaluations, proof-of-concept activities, product assessments, and implementation recommendations for enterprise networking and cybersecurity solutions. 6. Provides advanced technical support and consultation to business and IT stakeholders on complex network, infrastructure, and cybersecurity issues. Troubleshoots escalated network and security incidents, provides technical guidance to infrastructure teams, and educates IT and business personnel on security policies, secure configurations, access requirements, and risk mitigation practices. 7. Provides security expertise and technical leadership throughout the IT project lifecycle, including requirements development, architecture and design, implementation, testing, deployment, and operational support. Reviews project designs and proposed solutions to identify security risks and ensures appropriate security controls are incorporated into network, cloud, application, and infrastructure initiatives. 8. Designs, implements, and supports enterprise network infrastructure, including LAN/WAN, routing and switching, wireless networks, firewalls, VPNs, network segmentation, Internet connectivity, cloud connectivity, and data center infrastructure. Develops network solutions that support high availability, resiliency, scalability, and security requirements. 9. Leads the investigation and resolution of complex network and security incidents, utilizing network monitoring, logging, packet analysis, performance data, and security tools to identify root causes and implement corrective actions. Coordinates with vendors, technical teams, and organizational stakeholders during critical incidents and service disruptions. 10. Develops network security architecture and segmentation strategies designed to limit lateral movement, protect critical systems, isolate sensitive workloads, and establish appropriate security boundaries between users, applications, devices, and infrastructure. Evaluates east-west and north-south traffic flows to identify security risks and opportunities for improved network controls. 11. Establishes and monitors network performance and security metrics to identify trends, capacity requirements, vulnerabilities, and potential operational risks. Develops dashboards, key performance indicators, and management reports to support data-driven infrastructure and security decisions. 12. Maintains technical documentation and configuration standards for network and security infrastructure, including network diagrams, IP addressing, VLANs, firewall rules, access controls, security configurations, operational procedures, and disaster recovery requirements. Ensures documentation remains accurate and aligned with the current enterprise environment. 13. Collaborates with architecture, cybersecurity, systems, database, application, cloud, telecommunications, and infrastructure teams to develop integrated technology solutions. Serves as a senior technical resource and provides guidance on enterprise networking, security architecture, infrastructure design, and technology modernization. 14. Provides technical leadership and mentoring to network and security staff, establishes network engineering standards and best practices, reviews technical solutions, and assists with the development of team capabilities in enterprise networking, cybersecurity, cloud infrastructure, and emerging technologies. Senior-Level Requirements Must have extensive knowledge and demonstrated experience in enterprise networking, cybersecurity, systems, databases, cloud infrastructure, and/or Web operations. The senior-level Network Engineer is responsible for developing and implementing enterprise network and security strategies, leading complex technical projects, designing secure and resilient infrastructure, resolving the most complex network and security issues, conducting risk assessments, evaluating emerging technologies, and providing technical guidance to IT and business leadership. The position requires advanced knowledge of network architecture, routing and switching, firewalls, VPN technologies, network segmentation, wireless infrastructure, cloud networking, identity and access management, security monitoring, incident response, vulnerability management, disaster recovery, and enterprise security controls. 8 Job Specific Skills and Abilities (KSAs): Intermediate professional level role. Works independently or on multiple IT security projects as a project team member, occasionally as a project leader. Works on small to large, complex security issues or projects that require increased skill in multiple IT functional areas. May coach more junior staff. 9 General Knowledge Skills and Abilities (KSAs): The submitted candidate must be able to apply common knowledge, skills, and abilities in the following areas: 1. Communication: Have the ability to clearly convey information, in both written and verbal formats, to individuals or groups in a wide variety of settings (i.e.; project team meetings, management presentations, etc.). Must have the ability to effectively listen and process information provided by others. 2. Customer Service: Works well with clients and customers (i.e.; business office, public, or other agencies). Able to assess the needs of the customer, provide information or assistance to satisfy expectations or resolve a problem. 3. Decision Making: Makes sound, well-informed, and objective decisions. 4. Flexibility: Is open to change, new processes (or process improvement), and new information. Has the ability to adapt in response to new information, changing conditions . click apply for full job details