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Overview: SimVentions, consistently voted one of Virginia's Best Places to Work, is looking for aTest Engineerto join our Submarine-Launched Ballistic Missile (SLBM) team at the Naval Surface Warfare Center Dahlgren Division (NSWCDD) in Dahlgren, VA. In this full-time, on-base role, you will design and maintain automated test scripts, develop detailed test plans and cases tied to requirements, execute manual and automated testing across multiple levels, and collaborate with developers and government customers to identify and resolve software defects. The ideal candidate has at least 2+ years of software/systems testing experience, proficiency in test automation and Linux environments, strong requirements traceability skills, and excellent communication abilities for daily customer interaction and occasional technical presentations. U.S. citizenship is required, as well as willingness to work 5 days/week on-site at NSWC-Dahlgren. Travel: An ACTIVE Secret Clearance is required for this position. Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information. US Citizenship is required to obtain a clearance. Requirements: 2+ years of professional software/systems testing experience or equivalent education Experience running/writing automation scripts or code Comfortablility reviewing C++ code Experience using Linux systems Proven analytical ability to find, document, and help resolve complex software issues Experience linking requirements to test cases and managing test artifacts Excellent written and verbal communication; comfortable presenting to customers Strong teamwork and the ability to manage multiple tasks with limited supervision Responsibilities: Design, develop, and maintain automated test scripts and frameworks Write detailed test plans, test descriptions, and test cases tied directly to requirements Execute manual and automated testing (static, dynamic, integration, and system-level) Perform requirements traceability using DOORS and other tools Identify, document, and track software defects; collaborate closely with developers for rapid resolution Review peers' test documentation and provide constructive feedback Participate in Agile Sprint meetings and Configuration Control Board (CCB) activities Interface directly and professionally with government customers daily Occasionally present technical testing documentation Preferred Skills and Experience: Prior NSWCDD or other DoD lab experience U.S. Navy fleet experience with weapons or combat systems (Aegis, SSDS, etc.) Formal Qualification Testing (FQT), Verification&Validation (V&V), or shipboard testing background Expertise with DOORS, Jira, Azure DevOps, Git, or similar tools Familiarity with Configuration Management processes and CCB support Experience testing real-time or safety-critical systems Education: BS degree in Computer Science, Software Engineering, Cyber Security, or equivalent Navy experience is required. Compensation: Compensation at SimVentions is determined by a number of factors, including, but not limited to, the candidate's experience, education, training, security clearance, work location, skills, knowledge, and competencies, as well as alignment with our corporate compensation plan and contract specific requirements. The projected annual compensation range for this position is $70,000 - $98,000 (USD). This estimate reflects the standard salary range for this position and is just one component of the total compensation package that SimVentions offers. Benefits: At SimVentions, we're committed to supporting the total well-being of our employees and their families. Our benefit offerings include comprehensive health and welfare plans to serve a variety of needs. We offer: Medical, dental, vision, and prescription drug coverage Employee Stock Ownership Plan (ESOP) Competitive 401(k) programs Retirement and Financial Counselors Health Savings and Health Reimbursement Accounts Flexible Spending Accounts Life insurance, short-&long-term disability Continuing Education Assistance Paid Time Off, Paid Holidays, Paid Leave (e.g., Maternity, Paternity, Jury Duty, Bereavement, Military) Third Party Employee Assistance Program that offers emotional and lifestyle well-being services, to include free counseling Supplemental Benefit Program Why Work for SimVentions?: SimVentions is about more than just being a place to work with other growth-orientated technically exceptional experts. It's also a fun place to work. Our family-friendly atmosphere encourages our employee-owners to imagine, create, explore, discover, and do great things together. Support Our Warfighters SimVentions is a proud supporter of the U.S. military, and we take pride in our ability to provide relevant, game-changing solutions to our armed men and women around the world. Drive Customer Success We deliver innovative products and solutions that go beyond the expected. This means you can expect to work with a team that will allow you to grow, have a voice, and make an impact. Get Involved in Giving Back We believe a well-rounded company starts with well-rounded employees, which is why we offer diverse service opportunities for our team throughout the year. Build Innovative Technology SimVentions takes pride in its innovative and cutting-edge technology, so you can be sure that whatever project you work on, you will be having a direct impact on our customer's success. Work with Brilliant People We don't just hire the smartest people; we seek experienced, creative individuals who are passionate about their work and thrive in our unique culture. Create Meaningful Solutions We are trusted partners with our customers and are provided challenging and meaningful requirements to help them solve. Employees who join SimVentions will enjoy additional perks like: Employee Ownership:Work with the best and help build YOUR company! Family focus:Work for a team that recognizes the importance of family time. Culture:Add to our culture of technical excellence and collaboration. Dress code:Business casual, we like to be comfortable while we work. Resources:Excellent facilities, tools, and training opportunities to grow in your field. Open communication:Work in an environment where your voice matters. Corporate Fellowship:Opportunities to participate in company sports teams and employee-led interest groups for personal and professional development. Employee Appreciation:Multiple corporate events throughout the year, including Holiday Events, Company Picnic, Imagineering Day, and more. Founding Partner of the FredNats Baseball team:Equitable distribution of tickets for every home game to be enjoyed by our employee-owners and their families from our private suite. Food:We have a lot of food around here! FTAC

Job Description Job Description Job Title: Network Engineer Type: Contract to Hire (initial contract duration thru 12/30/2026) Location: Milwaukee, WI (hybrid Tues/Thurs onsite plus occasional travel to other locations - mileage reimbursed for those drives) Description: Requirements: MAIN MUST HAVES - Layer 3 networking & Wireless Networking experience. Must be in the SE Wisconsin area. Travel expected in SE Wisconsin, minimal travel outside of Wisconsin On-call rotation basis Daily queue support. Hybrid role, expected in the office on Tuesday and Thursday Can escalate to a tier 2 role, but needs to operate as the current Network Tier 1 team does (minimal escalations) Product knowledge preferred: Juniper/HPE (layer3 route/switch), Aruba wireless, Palo firewall and HPE SD Wan (nice to have but not needed). Good knowledge of othe products is a plus. Must be fluent in English, good communication skills Key Responsibilities Enterprise Network Engineering & Support: Provide operational support for enterprise network platforms, including switching, routing, firewalls, and wireless systems. Support enterprise wireless platforms through configuration, monitoring, performance tuning, and analytics. Diagnose and resolve network incidents. Assist with the design and implementation of network enhancements aligned with architectural and security best practices. Develop and execute test plans to validate network changes and deployments. Provide SD WAN support as needed for routing policies, monitoring, and connectivity. Hardware Lifecycle Management Manage lifecycle activities for a large inventory of network hardware, including switches, firewalls, wireless access points, and SD WAN devices. Coordinate planning and execution of hardware upgrades, refresh projects, and decommissioning efforts across multiple locations. Maintain accurate documentation of inventory, lifecycle stages, and platform dependencies. Collaborate with procurement teams, logistics, and field resources to ensure seamless deployment and transitions. Platform & Process Optimization Identify opportunities to improve network reliability, automation, documentation, and operational processes. Stay current with emerging networking technologies, industry trends, and best practices. Collaboration & Stakeholder Engagement Work closely with global and cross functional teams to understand requirements and deliver scalable solutions. Communicate technical information effectively to both technical and non technical stakeholders. Build and maintain strong working relationships across IT and business units. Documentation & Knowledge Development Create and maintain detailed documentation, including network diagrams, standards, lifecycle plans, and troubleshooting guides. Support change control processes and ensure accurate configuration management. Required Skills & Qualifications Strong hands-on experience with enterprise routing, switching, wireless platforms, and firewall technologies. Experience supporting large-scale network environments. Understanding of network security principles, segmentation, and best practices. Strong troubleshooting and analytical skills with experience conducting Root Cause Analysis. Excellent written and verbal communication skills. Understanding of change management practices. Ability to work effectively with cross-functional and global teams. Willingness to learn new tools, technologies, and methodologies. Preferred Qualifications Experience with automation-driven or template-based management platforms Experience working in a multi-vendor network Experience with structured lifecycle management processes and asset tracking. Understanding of the ITIL framework. Company Description Founded in 1990, Sunrise Systems is an award winning IT/Professional Staffing firm to Fortune 500 and State/Local Government Agencies. Company Description Founded in 1990, Sunrise Systems is an award winning IT/Professional Staffing firm to Fortune 500 and State/Local Government Agencies.

Sr. Distinguished AI Engineer At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex enterprise AI systems Demonstrated ability to lead and mentor an engineering organization and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience building and deploying multi-modal models for technologies like computer vision, speech recognition, optical character recognition, or other sensor systems in application such as robotics, digital assistants, industrial automation, autonomous driving, or related 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. Distinguished AI Engineer Richmond, VA: $286,200 - $326,700 for Sr. Distinguished AI Engineer New York, NY: $343,400 - $392,000 for Sr. Distinguished AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Distinguished AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Distinguished AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Distinguished AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Senior Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you'll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation). Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming languages like Python, Scala, or Java. Basic Qualifications: Bachelor's Degree At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 3 years of experience building, scaling, and optimizing ML systems At least 2 years of experience leading teams developing ML solutions Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing performant, resilient, and maintainable code 3+ years of experience with data gathering and preparation for ML models 3+ years of people management experience ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents 3+ years of experience building production-ready data pipelines that feed ML models Ability to communicate complex technical concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer Plano, TX: $209,000 - $238,500 for Sr. Lead Machine Learning Engineer Richmond, VA: $209,000 - $238,500 for Sr. Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Sr. Lead, Machine Learning Engineer (Enterprise Platforms Technology) As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. Enterprise Platforms Technology (EPTech) comprises many of Capital One's most important enterprise platforms. We play an essential role in establishing practices for building technology solutions across the company, while also delivering capabilities that exemplify those practices. What you'll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation). Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming languages like Python, Scala, or Java. Basic Qualifications: Bachelor's degree At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 3 years of experience building, scaling, and optimizing ML systems At least 2 years of experience leading teams developing ML solutions Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing performant, resilient, and maintainable code 3+ years of experience with data gathering and preparation for ML models 3+ years of people management experience ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents 3+ years of experience building production-ready data pipelines that feed ML models Ability to communicate complex technical concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer New York, NY: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Sr. Distinguished AI Engineer At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex enterprise AI systems Demonstrated ability to lead and mentor an engineering organization and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience building and deploying multi-modal models for technologies like computer vision, speech recognition, optical character recognition, or other sensor systems in application such as robotics, digital assistants, industrial automation, autonomous driving, or related 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. Distinguished AI Engineer Richmond, VA: $286,200 - $326,700 for Sr. Distinguished AI Engineer New York, NY: $343,400 - $392,000 for Sr. Distinguished AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Distinguished AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Distinguished AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Distinguished AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you'll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation). Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming languages like Python, Scala, or Java. Basic Qualifications: Bachelor's degree At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 2 years of experience building, scaling, and optimizing ML systems Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience building production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code 2+ years of experience with data gathering and preparation for ML models 2+ years of people leader experience 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer New York, NY: $215,200 - $245,600 for Lead Machine Learning Engineer Plano, TX: $179,400 - $204,700 for Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Senior Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you'll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation). Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming languages like Python, Scala, or Java. Basic Qualifications: Bachelor's Degree At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 3 years of experience building, scaling, and optimizing ML systems At least 2 years of experience leading teams developing ML solutions Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing performant, resilient, and maintainable code 3+ years of experience with data gathering and preparation for ML models 3+ years of people management experience ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents 3+ years of experience building production-ready data pipelines that feed ML models Ability to communicate complex technical concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer Plano, TX: $209,000 - $238,500 for Sr. Lead Machine Learning Engineer Richmond, VA: $209,000 - $238,500 for Sr. Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Lead Machine Learning Engineer (Enterprise Platforms Technology) As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you'll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation). Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming languages like Python, Scala, or Java. Basic Qualifications: Bachelor's Degree At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 2 years of experience building, scaling, and optimizing ML systems Preferred Qualifications: Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience building production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code 2+ years of experience with data gathering and preparation for ML models 2+ years of people leader experience 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer New York, NY: $215,200 - $245,600 for Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Sr. Lead, Machine Learning Engineer (Enterprise Platforms Technology) As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. Enterprise Platforms Technology (EPTech) comprises many of Capital One's most important enterprise platforms. We play an essential role in establishing practices for building technology solutions across the company, while also delivering capabilities that exemplify those practices. What you'll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation). Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming languages like Python, Scala, or Java. Basic Qualifications: Bachelor's degree At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 3 years of experience building, scaling, and optimizing ML systems At least 2 years of experience leading teams developing ML solutions Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing performant, resilient, and maintainable code 3+ years of experience with data gathering and preparation for ML models 3+ years of people management experience ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents 3+ years of experience building production-ready data pipelines that feed ML models Ability to communicate complex technical concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer New York, NY: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Overview The Lead Systems Engineer for High Performance Computing (HPC) and Artificial Intelligence (AI) works as part of the Advanced Systems team within Research Computing that supports the hardware and system-level software on the University's centralized high-performance computing and other computing for research systems. The Lead Systems Engineer is responsible for engaging with faculty, researchers, vendors, and other information technology (IT) staff to specify, design, install, and administer computing for research systems while also providing insight into trends and technologies supporting the advancement of AI research. The Lead Systems Engineer is also expected to be in tune to trends in computational research and will be asked to evaluate, pilot, and implement systems that advance Princeton's HPC and AI technologies enhancing Research Computing services. The Lead Systems Engineer serves as an expert for HPC and AI hardware and software and helps researchers troubleshoot system level problems with software, data, and job submission. This position requires one to work closely with colleagues at all levels of technical understanding in the Office of Information Technology (OIT) and University academic departments to provide timely and creative support for research computing. The Lead Systems Engineer is required to work well on teams and independently, and will be asked to lead initiatives within Advanced Systems, requiring only general supervision. On-call rotation is a mandatory facet of this role, requiring infrequent off-hour and weekend duty. Responsibilities Operations: Design, maintain, troubleshoot, and refine advanced HPC/AI cluster infrastructure including high performance interconnects, cluster schedulers, and configuration management across research systems. Partner with colleagues in Advanced Data and Storage Management to align designs for scratch filesystems and data management with cluster designs. Develop data-transfer pathways and networks to support AI driven computing workloads. Establish and maintain best practices for cluster management and usage to support AI-driven workloads. Develop documentation for users and technical staff that can be used by the larger community. Develop, enhance, and expand monitoring infrastructure and related protocols for research computing systems. Plan and implement scheduled maintenance of operations, including during off hours. Perform other tasks as assigned. Technical Leadership: Define and drive the institutional technical strategy for advanced AI and data intensive HPC. Bring creativity, foresight, and mature professional judgment in anticipating and solving novel and complex problems, in determining project objectives and requirements, and in developing standards and governance for all research computing platforms. Leveraging expertise in AI technologies, identify, evaluate, and pilot researcher-facing systems that enable the acceleration of research using AI. Lead the implementation and expand adoption of modern, automation-driven infrastructure and cluster management practices. Promote institution wide collaboration as the community expert advising and working with faculty, researchers and vendors on emerging trends and challenges in AI enabled research computing. Cultivate a collaborative, knowledge sharing environment by providing technical mentorship to systems specialists and analysts by sharing designs and operational expertise across data systems and HPC/AI infrastructure. Contribute to the strategic vision for HPC/AI systems; Advise senior leadership and stakeholders on strategic investments, risks, and opportunities related to research infrastructure. Troubleshooting and Problem Resolution: Monitor HPC clusters, networks, and storage systems for abnormalities, and resolve issues. Analyze and solve problems in Linux and HPC/AI computing environments with software, data, and job submissions. Use scripting and programming tools to troubleshoot issues. Qualifications Essential Qualifications: 10+ years of strong experience managing advanced research computing systems. Strong expertise with Linux system administration, installation, and troubleshooting. Advanced experience writing scripts in languages such as bash, Python and/or Perl. Proficient in managing networking in HPC environments. Strong experience managing software in an advanced research computing environment. Experience supporting scheduling and managing jobs (SLURM) in large-scale computing environments. Strong oral and written communication skills, with the ability to proactively engage peers and communicate effectively across a diverse stakeholder community. Strong ability to solve complex and system infrastructure problems, and share expertise with colleagues at all levels. Demonstrated ability to collaborate across teams to solve systems and infrastructure challenges, aligning day to day operational needs with longer term technical and organizational goals as technologies evolve. When provided access to personal, proprietary and/or otherwise confidential data, maintain such data in the strictest confidence and follow procedures to ensure the privacy, security, and proper use of data. Education: Bachelors degree in a related field or equivalent experience. Preferred Qualifications: Experience working in an academic and research settings. Experience supporting AI driven research in open and secure computing environments. Familiarity using and administering data-transfer technologies such as Globus that facilitate the transfer of large datasets. Experience using and supporting parallel file systems that are commonly used in HPC/AI systems. Experience supporting unstructured data in HPC/AI environments. Princeton University is an Equal Opportunity Employer and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law. The University considers factors such as (but not limited to) scope and responsibilities of the position, candidate's qualifications, work experience, education/training, key skills, market, collective bargaining agreements as applicable, and organizational considerations when extending an offer. The posted salary range represents the University's good faith and reasonable estimate for a full-time position; salaries for part-time positions are pro-rated accordingly. If the salary range on the posted position shows an hourly rate, this is the baseline; the actual hourly rate may be higher, depending on the position and factors listed above. The University also offers a comprehensive benefit program to eligible employees. Please see this link for more information. PIee63b3a5-by Jobble

Lead Machine Learning Engineer (Enterprise Platforms Technology) As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you'll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation). Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming languages like Python, Scala, or Java. Basic Qualifications: Bachelor's Degree At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 2 years of experience building, scaling, and optimizing ML systems Preferred Qualifications: Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience building production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code 2+ years of experience with data gathering and preparation for ML models 2+ years of people leader experience 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer New York, NY: $215,200 - $245,600 for Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Sr. Distinguished AI Engineer At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex enterprise AI systems Demonstrated ability to lead and mentor an engineering organization and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience building and deploying multi-modal models for technologies like computer vision, speech recognition, optical character recognition, or other sensor systems in application such as robotics, digital assistants, industrial automation, autonomous driving, or related 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. Distinguished AI Engineer Richmond, VA: $286,200 - $326,700 for Sr. Distinguished AI Engineer New York, NY: $343,400 - $392,000 for Sr. Distinguished AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Distinguished AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Distinguished AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Distinguished AI 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).

Location: 22525 SE 64th Pl, Suite 2026, Issaquah, WA 98027 and various unanticipated locations throughout the U.S Position Title: IT Business Systems Analyst (RLT36) Job Description: Analyze business processes, pain points, as-is system functionalities to provide recommendations on addressing business challenges. Define metrics and KPIs to measure success of strategic initiatives and report on their progress. Develop relationships and processes with sales, solution architects, solution delivery team, finance, partner, BD, and other cross-functional stakeholders. Define the key sales support systems/processes required to meet the rapid growth of the business and achieve revenue attainment and market development objectives. Identify root cause and improve system stability & scalability advocating best practice. Enhance data integrity through effective design, maintenance and security. Analyze data requirements for business models and be able to articulate requirements to Client's Integrations Team to enable automation on Anaplan. Work with the Enterprise System Management to determine the Anaplan roadmap and keep track of enhancements within individual projects and across initiatives, managing backlog. Work closely with our cross-functional partners to ensure that projects are completed on time and within budget. Coordinate testing with business and get UAT sign off. Support teams through all phases of the project including knowledge transition phase. Travel/relocate to various unanticipated locations throughout the U.S. for long- and short-term assignments at client sites. Multiple Positions Available. Job Requirements: Requires Masters degree or foreign equivalent in Computer Science, Engineering (any), Management (any), Business Administration or related. Travel and work at client sites as assigned. Travel/relocate to various unanticipated locations throughout the U.S. for long- and short-term assignments at client sites. 40 hours/week, 9:00am-5:00pm, Salary: $161,138- $161,138/year. Email resume with cover letter to ; referencing RLT36

Duration : 12 months We are looking for a motivated candidate for a Full-Stack Software Engineer role. These roles offer the chance to work with a cutting-edge tech stack and tackle complex, high-impact projects in the financial sector. Qualifications Bachelors or masters degree in Computer Engineering or equivalent with over 8+ years of experience. Required Skills: Proficiency in Java/Scala, Python and SQL. Experience with distributed data processing using Spark. Experience with databases technologies: Snowflake and Teradata preferably. Experience with cloud technologies (Azure, AWS, GCP). Experience with cloud compute technologies, Databricks. Experience with building data pipeline & ETL Development using Airflow. Experience with DevOps automation and CI/CD pipelines. Desired Skills: Knowledge of Power BI reporting is a plus. Experience with JavaScript frameworks is a plus. Experience with machine learning, GenAI and Agentic AI is a big plus. Non-technical Skills: Good problem solving and analytical skills. Excellent verbal and written communication skills. Ability to collaborate and interact with a global team and to deliver following strict timelines.

Job Description Job Description At Wilson Elser, we are redefining what it means to work at a national law firm. With more than 1,400 attorneys across 46 offices nationwide, we are recognized among the top 100 law firms by The American Lawyer and ranked in the National Law Journal's survey of the nation's largest law firms. Our continued success is built on a culture of collaboration, innovation, client service, and mutual respect. We are committed to fostering an environment where employees are empowered to grow their careers, contribute meaningfully, and thrive professionally. The Position We're looking for a Senior Network Engineer to own and evolve our enterprise network across multi-site and cloud environments. You'll be a key technical voice shaping infrastructure strategy, driving security posture through zero-trust principles, and ensuring high availability for business-critical systems - all while working remotely on a collaborative, senior-level team. Key Responsibilities Design & Architecture Architect scalable, resilient network solutions including routing/switching, SD-WAN, firewalls, VPN, QoS, and zero-trust segmentation. Define requirements, evaluate technologies, and lead infrastructure changes from design through implementation. Develop and maintain business continuity and disaster recovery plans for all network components. Operations & Maintenance Perform proactive maintenance - patching, upgrades, tuning, and health monitoring across the networking estate. Manage vulnerability findings and vendor security advisories for network equipment and systems. Maintain accurate network documentation, configuration baselines, and topology diagrams. Own and resolve network-related incidents and service requests, driving issues to resolution. Collaboration & Strategy Partner with security, infrastructure, and application teams to support firm-wide initiatives. Evaluate emerging technologies and translate their impact into actionable recommendations. Serve as a technical mentor and backup resource across the Network Engineering team. Communicate clearly with technical and non-technical stakeholders at all levels. Qualifications 10+ years of hands-on network engineering experience across multi-site enterprise environments Bachelor's degree in Computer Science, Information Technology, or a related field - or equivalent professional experience. Palo Alto Firewalls - Production deployment, policy management, and troubleshooting of Palo Alto NGFW (Panorama experience a strong plus). Cisco ACI - Hands-on experience with Nexus 9300/9000 series in ACI mode - fabric design, EPG/contract configuration, and troubleshooting. Proven ability to architect, implement, and troubleshoot complex, multi-vendor network infrastructure. Strong documentation habits - you leave networks better documented than you found them. Ability to translate ambiguous business requirements into clear, implementable technical designs. Excellent communication skills - comfortable presenting to both engineers and executives. Strong project management instincts with the ability to juggle multiple workstreams independently. A collaborative, team-first mentality balanced with the ability to drive work autonomously. Routing & Switching Deep expertise in enterprise routing protocols (OSPF, BGP) and switching (VLANs, port channels, spanning tree, QoS) across multi-site environments. Cisco certification at the professional or expert level (CCNP, CCDP, or CCIE) strongly preferred. Experience in professional services, financial services, or legal industry environments. Familiarity with network automation tooling (Ansible, Python/Netmiko, Terraform for network infra). Experience with public cloud networking (AWS, Azure) and hybrid connectivity patterns. Exposure to Panorama for centralized Palo Alto management at scale. Core Networking SD-WAN (Silver Peak / HPE Aruba EdgeConnect) - deployment, policy, and optimization DMVPN, IPSec VPN, and secure remote access architectures Load balancing (Citrix NetScaler / ADC) - configuration, SSL offload, and health monitoring Wireless networking via Cisco Meraki - deployment, RF planning, and troubleshooting Network tapping and packet capture solutions for visibility and forensics Security & Zero Trust Zscaler (ZIA/ZPA) - implementation, policy configuration, and troubleshooting ACL development and firewall policy lifecycle management Zero-trust network segmentation principles and implementation WAF configuration and proxy infrastructure Collaboration & Voice Cisco Call Manager (CUCM) and Unity Connection - administration and troubleshooting Network monitoring and management platforms (SolarWinds, PRTG, or equivalent) Wilson Elser offers a competitive salary and benefits package designed to support our attorneys both professionally and personally. A variety of factors are considered in making compensation decisions, including but not limited to experience, education, licensure and/or certifications, geographic location, market demands, other business and organizational needs, and other factors permitted by law. Final salary wages offered may be outside of this range based on other reasons and individual circumstances. This position is considered full-time and therefore qualifies for benefits including 401(k) retirement savings plan, medical, dental, vision, disability, and life insurance. Details of participation in these benefit plans will be provided if an employee receives an offer of employment. Salary Range: $135,000-$150,000 USD Why Should You Apply? Benefits: Outstanding benefits package, including 401k match and generous PTO plan Career Growth: Ample opportunities for professional development and advancement Employee Perks: Access to corporate discount plans and other benefits Wilson Elser welcomes submissions of candidates for our open positions exclusively from recruitment agencies with an active, signed fee agreement who have been granted access to a position through our dedicated Recruitment Agency Portal. We are unable to consider submissions from recruitment agencies without a current (dated as of 7/1/2024) agreement in place. We appreciate your understanding. For collaboration inquiries or to establish an agreement, please contact us at . Wilson Elser is committed to a collegial work environment in which all individuals are treated with respect and dignity. It is the Firm's policy that employment will be based on merit, qualifications, and competence. Further, employment decisions will be made without regard to an applicants race, color, age, sex, religion, creed, national origin, ancestry, citizenship, marital status, sexual orientation or preference, gender identity, physical or mental disability, status as a victim of domestic violence, sex offenses, or stalking, past or present service in the uniformed services or application or obligation to serve in the uniformed services, or any other characteristic protected by law. Wilson Elser endeavors to make the Wilson Elser website accessible to any and all users. You may review our Accessibility Policy here. California Residents may review our CCPA notice for applicants and employees here.

The opportunity Delaware North is hiring an Senior Platform Engineer to join our Technology team ideally at our global headquarters in Buffalo, New York. As a Senior Platform Engineer, you will design and support modern integration solutions that connect enterprise systems and enable secure, scalable delivery. If you want a fast-paced role where collaboration and hard work are rewarded, apply now. Pay Minimum - Anticipated Maximum Base Salary: $100,700 - $136,000 / year In addition to base salary, we offer an annual bonus plan based on company and individual performance, or a role-based, uncapped sales incentive plan. The advertised pay range represents what we believe at the time of this job posting, that we would be willing to pay for this position. Only in special circumstances, where a candidate has education, training, or experience that far exceeds the requirements for the position, would we consider paying higher than the stated range. Information on our comprehensive benefits package can be found at . What we offer At Delaware North, we care about our team members' personal and professional journeys. These are just some of the benefits we offer: Medical, dental, and vision insurance 401(k) with up to 4% company match Annual performance bonus based on level, as well as individual, company, and location performance Paid vacation days and holidays Paid parental bonding leave Tuition and/or professional certification reimbursement Generous friends-and-family discounts at many of our hotels and resorts What will you do? Design, develop, and maintain integration services using iPaaS and modern integration patterns Build and support APIs, event driven integrations, and data exchange across internal and external systems Improve platform reliability through monitoring, logging, alerting, and performance tuning Build, optimize, and maintain GitLab CI/CD pipelines, templates, and automation Troubleshoot production issues, perform root cause analysis, and implement long term fixes Collaborate with internal teams and third party vendors to deliver high quality solutions on time More about you Minimum of 5 years' experience in Java development and software engineering Experience building APIs and integrations using REST, messaging, batch, or event driven patterns Hands on experience with CI/CD pipelines, ideally using GitLab Experience working with cloud platforms such as AWS or Azure MuleSoft integrations design, development, and implementation experience a plus Strong understanding of software engineering best practices and secure development Ability to work effectively with cross functional teams and external partners Must be legally authorized to work in the US without sponorship Who we are Our business is all about people, and that includes you. At Delaware North, you're not just part of a team - you're part of a global legacy: a family-owned company with 100+ years of history behind it. Our operations span the world, offering you unique paths to growth and success. Who says you can't love where you work? With jobs in iconic sports arenas, stunning national parks, exciting casinos, and more, we pride ourselves on giving the world great times in great places. And whether you're interested in restaurants, hotels, sports, gaming, operations, or retail, part-time or full-time, we're invested in helping you achieve your career goals. Together, we're shaping the future of hospitality - come grow with us! Delaware North, along with its subsidiaries, is an equal opportunity employer, showcasing job opportunities and considering applicants for all positions without regard to race, color, religion, sex, gender identity, national origin, age, disability, protected veteran status, sexual orientation, or any other legally protected status. $100,700 - $136,000 / year

Job Description Job Description Applications Engineer II West Palm Beach, FL Full-Time Medical Device Manufacturing Help Build the Technology Behind Life-Saving Medical Devices Are you an engineer who enjoys solving complex technical challenges, working directly with customers, and turning innovative ideas into real-world manufacturing solutions? MMT is seeking an Applications Engineer II to join our growing team in West Palm Beach, Florida. In this role, you'll serve as a technical expert supporting advanced catheter manufacturing processes and equipment used to produce minimally invasive medical devices that improve and save lives. You'll work hands-on in our Applications Lab, collaborate with customers around the world, and partner with Engineering, R&D, and Production teams to develop cutting-edge manufacturing solutions. If you thrive in a fast-paced environment where no two projects are the same, this is an opportunity to make a direct impact on innovative medical technologies. What You'll Do As an Applications Engineer II, you will: Partner with customers to understand manufacturing challenges and recommend process and equipment solutions. Conduct proof-of-concept testing and process development in our Applications Lab. Develop, validate, and optimize manufacturing processes for catheter and medical device applications. Troubleshoot technical and process-related challenges and perform root cause analysis. Program, test, and validate equipment prior to customer acceptance and shipment. Prepare technical reports and present recommendations to customers and internal stakeholders. Collaborate with Engineering and R&D teams to improve machine capabilities, tooling, and automation. Train customers and internal teams on equipment operation, process control, and best practices. Support continuous improvement initiatives focused on quality, productivity, and innovation. What We're Looking For Required Qualifications Bachelor's degree in Mechanical, Electrical, Aerospace Engineering, or a related engineering discipline. 3+ years of experience in applications engineering, process engineering, manufacturing engineering, or a related technical role. Strong analytical, troubleshooting, and problem-solving skills. Ability to communicate technical information effectively to both technical and non-technical audiences. Experience reading and interpreting engineering drawings, schematics, and technical documentation. Ability to travel domestically and internationally up to 10-20%. Valid U.S. Passport or ability to obtain one. Preferred Qualifications Experience within medical device manufacturing. Experience with catheter manufacturing processes such as tipping, flaring, bonding, drilling, or related technologies. Knowledge of process validation, DOE, capability analysis, and statistical methods. Experience with CAD software such as AutoCAD, Inventor, SolidWorks, or similar. Familiarity with ISO 13485, FDA Quality System Regulations, and regulated manufacturing environments. Knowledge of polymers and materials used in catheter and tubing applications, including Pebax, Nylon, PTFE, and FEP. Why Join MMT? At MMT, you'll work alongside industry experts developing advanced manufacturing technologies that support some of the world's leading medical device companies. We offer: Meaningful work that contributes to life-saving medical innovations. Exposure to cutting-edge manufacturing technologies and automation. Opportunities to collaborate directly with customers and industry leaders. Career growth in a rapidly evolving, high-tech industry. A collaborative, team-oriented environment where innovation is encouraged. This role combines office, laboratory, and production-floor work. You'll have the opportunity to work hands-on with advanced manufacturing equipment, precision tooling, and process development projects while collaborating with teams across multiple disciplines. Occasional travel to customer sites is required. Ready to Make an Impact? If you're passionate about engineering, innovation, and helping bring life-saving medical technologies to market, we'd love to hear from you. Apply today and help shape the future of medical device manufacturing with MMT. Medical Manufacturing Technologies (MMT) is an equal opportunity employer. We are committed to creating an inclusive environment for all employees and applicants. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other protected characteristic under applicable law. MMT is committed to providing reasonable accommodations to qualified individuals with disabilities. If you need assistance or accommodation during the application or interview process, please contact us. MMT participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the United States. PIe7b3545cc5-

Description: Base Salary Range: $150K - $180K Reports to - VP of Engineering Annual Bonus: Yes Direct Reports - Controls Engineers Remote: No Status - Exempt Company Website: ABOUT SCHNEIDER At Schneider Packaging Equipment Company, Inc. ("Schneider"), we believe innovation starts with the consumer. This approach has propelled our success in developing real-world solutions that allow us to automate the supply of life's products. With over 50 years of industry problem-solving in end-of-line automation, Schneider is a leading manufacturer of case packing and robotic palletizing solutions. Headquartered in Upstate New York, we design state-of-the-art machinery for customers in industries such as: food and beverage, dairy, pharmaceutical, personal care, plastics, and paper. Schneider is now a part of the Pacteon family of companies. Our continued growth has allowed us to really be our Customer's one source for end of line packaging solutions. ABOUT PACTEON Pacteon Group provides one source for best-in-class automation focused on end of line packaging solutions, providing the highest-level customer experience. Through a broad range of robotic and non-robotic equipment, ability to integrate solutions seamlessly across portfolio companies, and full sales and service coverage, Pacteon is uniquely positioned to design flexible and custom solutions for your automation needs. For more information on Pacteon, please visit . OUR CORE VALUES We believe and live our Core Values, our IPACT: Integrity Pride Accountability Customer Service Teamwork Our Pacteon Promise is "We make it right". As our customer's one source for end-of-line packaging solutions, everyone plays an important role to make that happen. We provide internal growth paths for our employees and support them in their professional development goals. Diversity is important to us; we are proudly an Equal Opportunity Employer striving for innovation and growth both for our employees and our Company. SUMMARY AND PURPOSE The Senior Controls Engineering Director provides strategic leadership, operational oversight, and technical governance for the entire controls and automation engineering department. This role transitions from executing individual projects to scaling engineering capabilities, standardizing global design practices, and aligning automation technologies with overarching business growth strategies. KEY RESPONSIBILITIES Strategic Leadership & Governance Define global standards: Establish, enforce, and evolve company-wide controls engineering design standards and safety practices. Technology roadmap: Identify, lead development, and integrate emerging automation technologies, robotics advancements, and industry 4.0 trends. Operational excellence: Continuously refine engineering processes to maximize production velocity, reduce defects, and streamline costs. Budget ownership: Manage Research and Development, capital expenditure, and operational expenditure (R&D/CapEx/OpEx) budgets for the controls engineering department. Departmental & Project Oversight Portfolio management: Monitor engineering execution across all simultaneous projects to guarantee scope, timeline, and margin compliance. Resource allocation: Optimize workforce planning, assigning engineering talent effectively across concurrent machine builds and R&D efforts. Escalation authority: Serve as the final technical arbiter for complex engineering challenges, field failures, and design deadlocks. Talent cultivation: Build engineering capabilities through structured mentorship, continuous education programs, and performance management. Cross-Functional Integration & Commercial Support Sales enablement: Partner with Applications Engineering to review high-risk pricing models, concepts, and technical proposals. Manufacturing alignment: Streamline workflows between applications, design engineering, electrical assembly, shop-floor commissioning, and final factory acceptance. Executive collaboration: Align engineering capabilities with corporate business strategies, product management, and supply chain operations. Key account management: Act as the senior technical representative during high-stakes customer consultations and critical site escalations. Field Operations & Travel Global commissioning strategy: Oversee the site-acceptance testing (SAT) framework to ensure flawless customer handovers. Strategic field deployment: Travel to customer sites, trade shows, or vendors (approx. 15-20%) for high-level executive reviews or critical system resolutions. Compliance maintenance: Maintain a valid passport and enhanced driver's license for frictionless international travel. Requirements: PROFESSIONAL QUALIFICATIONS Education & Experience: BS in electrical engineering, automation engineering, or equivalent technical field. 10+ years of engineering experience within a design-build capital equipment manufacturing environment as a controls or electrical engineer. 5+ years of direct people management experience leading multi-disciplinary engineering teams. Project management experience preferred Core Skills & Competencies: Executive acumen: Proven track record scaling engineering departments, managing budgets, and executing corporate strategy. Project governance: Advanced understanding of Project Management Professional (PMP) principles or complex lifecycle management (PLM) systems. Technical mastery: Deep legacy knowledge of industrial automation architectures, advanced robot simulation, PLCs, HMIs, and SCADA systems. Experience with Rockwell Allen Bradley PLC and HMI platforms (Optix/Studio/ RSLogix5000, FactoryTalk View Studio) to program and control industrial machinery or processes. Experience with Fanuc robotics platform. Experience selecting and designing hardware to control and monitor industrial machinery and/or industrial processes Experience with integration into WES, MES platforms a plus. Experience with integration into track and trace systems a plus. Experience with industrial vision programming (i.e. Cognex/Keyance) a plus. Relevant codes such as NFPA 79, NFPA 70, and CE a plus. Ability to interpret and to generate electrical and pneumatic schematics in ACADE or equivalent Microsoft platform and relevant design and life cycle management software. PHYSICAL REQUIREMENTS & WORK REQUIREMENTS Physical Requirement Never Sometimes Frequently Sitting X Standing/Walking X Lifting/Carrying Upto 10 lbs X Lifting/Carrying Upto 30 lbs X Pushing/Pulling X Keyboarding X Gross Manipulation X Fine Manipulation X Driving X Stooping X Speaking X Hearing X Near Visual Acuity X Ability To Travel X Compensation details: 00 Yearly Salary PIc9a847df8c0d-1144