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Job Description We are searching for a Systems Administrator to join the Reston, VA location of the Digital Engineering Department in the Cyber, Modeling, and Simulation Division of the Information Advantage Office at the Applied Research Laboratory (ARL) at Penn State. You will maintain the integrity of various high-performance computing (HPC) systems including operating systems, physical servers/workstations, and applications; administer, install, and troubleshoot a variety of Cloud tooling and applications, perform systems maintenance tasks such as troubleshooting and performance evaluation as well as back-up and recovery; perform configuration changes to address customer needs; schedule, install, and test system software upgrades; monitor and maintain software licensing. ARL is an authorized DoD SkillBridge partner and welcomes all transitioning military members to apply You will: Install, configure, maintain, upgrade, and support systems and software with a focus on Linux (Red Hat), Ansible scripting, and GitLab pipelines Develop plans, schedules, and requirements for deployment of systems Create or improve existing scripts and tooling to aid in systems management Diagnose, troubleshoot, and resolve server, workstation, and audio-visual (A/V) issues and/or respond to outages during normal working hours Resolve service-related issues; determine immediate economic and financial consequences of an incident Test and implement upgrades and patches to installed operating systems, software container orchestration platforms (Kubernetes), and modeling & simulation (M&S) applications Maintain reliability of systems by monitoring, running tests, and troubleshooting Monitor backups and plans for installed systems Monitor, maintain, and execute automation processes and CI/CD pipelines Evaluate and recommend new or existing system improvements and/or solutions Create and maintain system documentation of our processes, procedures, plans, and configurations May supervise staff members, including hiring, development, and performance management Required Skills/Experience areas to include: Ability to install, configure, maintain, upgrade, and support systems and software, with a strong focus on Linux (Red Hat), Ansible scripting, and GitLab pipelines Skilled in diagnosing, troubleshooting, and resolving server, workstation, and audio-visual (A/V) issues, including responding to system outages during normal business hours Proficiency in testing and implementing upgrades and patches for operating systems, Kubernetes-based container orchestration platforms, and modeling and simulation (M&S) applications Current eligibility for access to classified information at the Secret level or higher and may be subject to a government background investigation to upgrade clearance eligibility, if required Your working location will be fully onsite, located in Reston , VA.

Job Description Our valued client in the Denver Tech Center is seeking a Sr. Platform Engineer for their team. This is a hybrid role that requires you to reside in the Denver-Metro area. This engagement is a six-month contract-to-hire opportunity. Position Summary A senior, hands-on platform engineer with ownership across the whole internal developer platform: infrastructure, CI/CD, observability, security, and cost, not just one slice of it. This role carries more scope and more independent judgment than the Platform Engineer role, and may informally point the technical direction for other engineers on a given project, without a formal management title. Key Responsibilities • Own the internal developer platform (IDP): drive the design and evolution of the self-service workflows, the Golden Paths, that the rest of engineering relies on • Lead infrastructure as code practice: set the standard for how the team provisions and manages infrastructure, and build the automation others follow • Own CI/CD architecture: design and evolve the build, test, and deployment pipelines the platform depends on, including how GitOps practices get applied • Drive observability strategy: make sure the platform is monitored, logged, and traced well enough that problems surface before anyone has to ask • Own performance reporting: build and maintain the metrics and reporting layer that shows leadership and the rest of the organization how the platform is performing month to month • Set the security and access standard: establish how secrets, access control, and role-based access control (RBAC) get handled across the platform • Own platform cost and efficiency: track spend and bring cost-efficiency recommendations forward • Guide other engineers: give informal technical direction and review to the rest of the team Required Qualifications • Programming and automation: strong Python skills and a track record of building real automation and integrations at production scale • Cloud and containers: deep experience with a major cloud provider (AWS or Azure) and containerized infrastructure running in production • CI/CD and delivery practices: considerable experience owning pipelines end to end, including secure, modern deployment practices • Infrastructure as code at scale: experience running IaC practices, such as Terraform, across a real production environment • Security mindset: bake security into everything you build and hold the rest of the team to the same standard • Cost awareness: experience applying FinOps or similar cost-management practices to cloud spend at scale • Reporting and transparency: track record of building metrics or reporting capability that gives leadership and other teams real visibility into platform performance • Working with developers: track record of treating the platform's users as customers and adjusting the platform based on their feedback Preferred Qualifications • Experience informally mentoring or guiding other engineers • Experience with hybrid on-premises and cloud environments • Experience with observability or log management platforms • Exposure to cloud cost management or FinOps practices Certifications are a plus but not required. Hands-on experience is weighted more heavily

Description: JOB DESCRIPTION Job Title: Applications Engineer ABOUT OMI INDUSTRIES At OMI Industries, we are committed to using the natural power of plant oils to produce safe, natural, and effective odor removing products without the use of harsh chemicals or artificial fragrances. With over 30 years of expertise, OMI is the world leader in manufacturing natural odor eliminating solutions for industrial, commercial, and consumer applications. We are looking for a motivated Applications Engineer to join our growing Ecosorb team! JOB PURPOSE The Applications Engineer will organize and manage Ecosorb treatment applications and design approaches to treat customer odors using Ecosorb. This role will work to grow into an odor control expert with an understanding of the application of existing odor control technologies in different scenarios and industries. This individual will report to OMI's Director of Industrial Sales and will collaborate with Research & Development, Operations, Sales, and Service team members. JOB RESPONSIBILITY SUMMARY Analyze customer sites via 3D models, drawings, Google Earth, Photos, Sales/Field Tech notes, and onsite visits. Provide necessary details to drafter for application drawing. Combine theoretical, practical, and testing to achieve the best possible outcomes for our customers. Recommend the best approach to fight odors with Ecosorb treatment. Combine theoretical, practical, and testing to achieve the best possible outcomes for our customers. Travel to customer sites to learn about, evaluate, and improve odor treatment applications. Prepare and deliver presentations about Ecosorb solutions and their effectiveness. Develop techniques to assess and validate the application designs. Manage and update customer application information in Salesforce CRM system. Troubleshoot systems and make small repairs on-site as needed with support from equipment team. Recommend improved application approaches, chemistry and/or equipment, to customers and explain how changes will increase efficiency. Evaluate competitive odor control technology and build comparisons data sets, such as pro/con, strengths/weaknesses, and application area focuses. Collaborate with the Equipment team, Service team, R&D, and Director of Industrial Sales to create efficient systems. Other duties as assigned. Requirements: KEY COMPETENCIES: Systems thinker; able to look at a complex process, understand what the variables are, and how to adjust the variables to reach your desired result. Application engineering and solution architecture: take vague information from customers and sales and translate that into an application approach with clear variable and risk definitions Communication: Articulating thoughts and ideas clearly and effectively in written and oral forms to people of ranging skillsets. People skills: Building relationships and effectively communicating with other members of the OMI team. Time management: Ability to hold self and others accountable for key deliverables. Mechanical aptitude: base knowledge of tools and parts. REQUIRED KNOWLEDGE, SKILLS, & ABILITIES (To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skills, and ability required.) Bachelor's degree in chemical engineering, or equivalent educational experience in Chemistry, Fluid Dynamics, and Thermodynamics. 0+ years' experience. Proficient in all Microsoft Office suite; Word, Excel, PowerPoint, OneNote, Teams. Ability to learn new software systems such as Salesforce CRM, Photogrammetry, SolidWorks, etc. Understanding of fluid dynamics, chemistry, physics, math, and construction applied to product design and systems. Ability to write presentations, letters, and formulate proposals. Collaborative approach with ability to lead across and communicate with all types of functions. (Sales, Marketing, Finance, Operations, Human Resources, Senior Leadership, etc.). TRAVEL/ATTENDANCE: Applications Engineer will work in our Palatine, IL office. Hybrid Schedule of Monday/Friday Remote and Tuesday-Thursday in the office. Frequent travel is required to visit customers, attend trade shows and participate in internal meetings. The expected overnight CH1 travel in this position is 4-6 days per month but may fluctuate based on business needs. PHYSICAL REQUIREMENTS/HAZARDOUS WORKING CONDITIONS (The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of the job. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential work functions.) OMI Industries manufactures odor eliminating solutions. Chemical exposure to raw materials including plant oils, fragrances, and other materials will occur. The employee will be expected to travel to customer sites including but not limited to asphalt plants, wastewater treatment facilities, and industrial refineries. The employee will be regularly required to sit; stand; walk; bend; climb; kneel; crouch; and reach using feet, legs, back, arms, hands; to talk and hear. The employee must be capable of wearing required Personal Protective Equipment such as hard hats, safety glasses, gloves, steel-toed boots, hearing protection, and respiratory protection (including face masks and respirators). While on customer sites, the employee must be able to ascend/descend ladders and stairs, access rooftops, confined spaces, and uneven terrain. The employee must be able to adhere to, evaluate, and act on safety protocols. They must have a tolerance for the state of sites (I.e., smell, odor, dirt). Must possess the ability to detect auditory and/or visual alarms. WORK ENVIRONMENT: Work may be outdoors in a variety of weather conditions and environments with potential exposure to moving mechanical parts, hazardous substances, and biological waste. PI0c1501c7deb7-2247

Job Description Job Title: Senior AI Engineer - AI Solutions & Validation Frameworks Experience: 8+ years Domain: AI / Generative AI / Enterprise Solutions Role Overview We are looking for an AI Engineer with 8+ years of professional experience in designing, developing, validating, and implementing AI solutions for enterprise use cases. The candidate will work directly with clients and internal stakeholders to understand business requirements, translate them into technical solutions, define solution validation approaches, and drive implementation. An important aspect of this role will be to help design and establish a standardized, reusable AI validation framework that can be applied across different AI solutions and projects within the organization. This includes defining evaluation methodologies, validation criteria, performance metrics, testing processes, and quality benchmarks to ensure the reliability, accuracy, and effectiveness of AI solutions. The ideal candidate should combine hands-on AI engineering capabilities with strong communication, problem-solving, and stakeholder management skills. Required Skills & Qualifications 6+ years of professional experience in AI/ML engineering, Generative AI development, or implementation of AI-driven or analytical solutions. Demonstrated experience designing, developing, and implementing AI solutions in real-world business or enterprise environments. Strong understanding of Generative AI concepts, LLMs, prompt engineering, and RAG architectures. Hands-on experience with Python and relevant AI/ML frameworks and libraries. Experience with LangChain, LangGraph, LlamaIndex, or similar frameworks. Understanding of AI evaluation methodologies, testing approaches, model performance metrics, and validation techniques. Experience working with APIs, databases, structured and unstructured data, and enterprise application integrations. Ability to translate business requirements into technical solution designs and implementation plans. Strong communication skills and the ability to interact directly with clients and business stakeholders. Ability to work independently, manage multiple priorities, and collaborate with cross-functional teams. Preferred Qualifications Experience developing reusable AI evaluation or validation frameworks. Familiarity with LLM evaluation tools and frameworks such as RAGAS, DeepEval, TruLens, LangSmith, or equivalent. Experience with automated testing, CI/CD integration, and monitoring of AI applications. Knowledge of AI guardrails, hallucination detection, responsible AI, and output quality assessment. Experience implementing enterprise GenAI solutions across multiple business functions. We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, citizenship status, age, disability, genetic information, protected veteran status, or any other characteristic protected by applicable law. verify.gov/sites/default/files/everify/posters/IER_RighttoWorkPoster.pdf

Job Description Senior Engineer, Machine Learning Compensation: $130,000-$140,000 + 6% Annual Bonus The Senior Engineer, Machine Learning will lead the development, testing, validation, and deployment of machine learning models that improve product performance, installation quality, outage detection, and equipment reliability. This role focuses on analyzing large-scale data generated by millions of deployed meters, sensors, radios, and connected devices to identify performance issues, detect anomalies, and drive actionable solutions. A critical requirement for this position is hands-on experience personally building and training machine learning models, along with implementing anomaly detection algorithms within those models. Candidates must have direct experience developing these models, not simply using existing models or supporting another team's development efforts. Explore the Depth of the Role Machine Learning Model Development Personally build, train, test, and deploy machine learning models, including predictive models, classifiers, and anomaly detection algorithms. Develop time-series data mining and anomaly detection solutions to identify unusual behavior, performance degradation, and potential equipment failures. Design and maintain end-to-end machine learning pipelines, from data preparation and model training through validation, deployment, and production monitoring. Monitor model performance, identify model drift, and implement improvements to maintain accuracy and reliability. Establish testing and validation methods to confirm model results against real-world data. Integrate model outputs into reporting tools and dashboards to support engineering and customer-facing teams. Technical Leadership & Collaboration Lead machine learning projects and investigations, defining technical requirements, scope, schedules, and deliverables. Establish model development standards and validation criteria. Mentor engineers and provide guidance on data preparation, model development, and deployment practices. Collaborate with software developers, data engineers, data scientists, and reliability and quality engineering teams. Communicate technical findings and recommendations to leadership and non-technical stakeholders. Data Infrastructure & Integration Develop and maintain data pipelines integrating internal and external sources, including sensor, carrier network, weather, and manufacturing test data. Work with AWS cloud infrastructure and machine learning platforms, including SageMaker, S3, EC2, ECS, and Glue. Utilize data technologies such as Elasticsearch, Amazon Redshift, and NoSQL databases. Support scalable data architecture and near-real-time analysis of large-scale time-series datasets. Qualifications: Education Bachelor's or Master's degree in Engineering, Mathematics, Statistics, Computer Science, Data Science, Data Analytics, or a related field. Equivalent practical experience may be considered. Required Experience & Technical Skills 5+ years of experience in machine learning, data science, or applied analytics. Demonstrated experience personally building and training machine learning models. Direct experience implementing anomaly detection algorithms within machine learning models you have developed. This is mandatory. Strong proficiency in Python and SQL. Experience with predictive modeling, classification, statistical modeling, and time-series analysis. Experience working with large-scale sensor, IoT, endpoint, or other time-series data. Experience designing, validating, deploying, and monitoring machine learning models in production. Familiarity with GitHub, Jupyter Notebooks, and data visualization tools. Experience with cloud-based machine learning platforms, preferably AWS. Familiarity with Elasticsearch, Amazon Redshift, Grafana, and NoSQL data stores. Preferred Qualifications Experience with IoT devices, meters, sensors, radios, or connectivity equipment. Experience managing machine learning pipelines from development through production monitoring. Understanding of product reliability, device hardware, and failure analysis. Experience integrating third-party data sources into machine learning pipelines. Ability to independently lead technical projects and communicate complex findings. Familiarity with Lean Six Sigma or other continuous improvement methodologies. Competitive Total Rewards Competitive base salary of $130,000-$140,000 plus a 6% annual bonus. Eligible for annual pay increases. Comprehensive health, vision, and dental coverage. 15 days of paid time off plus 11 paid holidays. Retirement savings plan with a 25% employer match on contributions up to 7% of eligible compensation. Additional employer contribution of 5% of eligible compensation to a Defined Contribution account annually. Access to a certified financial planner at no cost. Employer-paid basic life insurance, short-term disability, and Employee Assistance Program. Tuition reimbursement up to $5,250. Voluntary life insurance, long-term disability, accident, and critical illness coverage. Health Savings Account (HSA) and Flexible Spending Account (FSA) options.

Job Description Job Summary Neutrino Advisory is looking for a Senior Analytics Engineer to help build modern, scalable, and trusted data foundations that enable organizations to make better business decisions. In this role, you will design, build, and maintain transformation and semantic layers that convert raw data from enterprise platforms into governed, well-tested, documented, and business-ready datasets and metrics. You will play a key role in enabling both centralized and self-service analytics, ensuring that analysts, business stakeholders, and AI-enabled tools can access and generate trustworthy insights from enterprise data. The ideal candidate brings strong software engineering discipline to analytics development, including version control, automated testing, code reviews, and continuous integration and deployment. You will work closely with business stakeholders, data engineers, BI developers, and technology teams to establish best practices and deliver high-quality data products. This is a hands-on senior-level role with opportunities to influence architecture, establish engineering standards, mentor team members, and contribute to Neutrino's growing Data & Analytics practice. Key Responsibilities • Design, develop, and maintain dbt models on Microsoft Fabric, transforming raw source data into clean, well-documented staging, intermediate, and mart layers using consistent modeling standards and naming conventions. • Design and co-own Power BI semantic models, including certified datasets, shared measures, and row-level security, ensuring consistent metric definitions across reports, dashboards, and self-service analytics. • Establish and implement data quality standards through dbt tests, source freshness checks, data contracts, monitoring, and alerting mechanisms. • Implement software engineering best practices for analytics development, including Git-based workflows, pull request reviews, automated CI/CD for dbt and Fabric deployments, and environment management across development, testing, and production. • Collaborate with business stakeholders, finance, operations, and technology teams to translate business requirements into reliable data models, metrics, and analytical solutions. • Establish clear documentation for data models, metrics, business definitions, and data lineage to enable analysts, business users, and AI-powered tools to discover and confidently use enterprise data. • Develop and maintain a catalog of certified datasets, business metrics, and data ownership. • Optimize data transformation pipelines and semantic models for performance, scalability, and cost through incremental loading, partitioning, and efficient query design. • Apply appropriate data access controls, privacy protections, security standards, and auditability requirements in collaboration with information security and compliance teams. • Review technical deliverables, mentor junior analysts and engineers, and promote best practices in analytics engineering and data modeling. • Contribute to the development of reusable templates, technical standards, frameworks, and onboarding documentation. • Evaluate emerging tools, technologies, and architectural approaches to continuously improve the data and analytics ecosystem. • Troubleshoot complex data and pipeline issues, conduct root cause analysis, and communicate resolutions and business impact effectively to technical and non-technical stakeholders. Required Knowledge, Skills & Qualifications • Bachelor's degree in Computer Science, Engineering, Data Science, Statistics, Information Systems, or a related field, or equivalent practical experience. • 6+ years of experience in Analytics Engineering, Data Engineering, or Business Intelligence development, with demonstrated experience delivering production-grade data models. • Advanced SQL skills, including query optimization, dimensional modeling, fact and dimension tables, and slowly changing dimensions (SCD). • Hands-on experience with dbt in production environments, including modular model development, testing, documentation, macros, incremental models, and deployment practices. • Experience with Microsoft Fabric, including Lakehouse, Warehouse, OneLake, Data Factory, and data pipelines, or comparable cloud data platforms such as Snowflake, Databricks, or BigQuery. • Strong Power BI experience, including semantic model design, DAX, row-level security, and governance of shared datasets. • Familiarity with AI-enabled analytics tools and the data architecture, governed metrics, metadata, and documentation required to support reliable AI-driven insights. • Working knowledge of Git, pull request workflows, and CI/CD pipelines using tools such as Azure DevOps or GitHub Actions. • Proficiency in Python for scripting, automation, and data validation. • Experience implementing data quality, testing, monitoring, and observability practices. • Ability to translate complex or ambiguous business requirements into clear technical designs and communicate architectural decisions and trade-offs effectively. • Strong written and verbal communication skills, with the ability to collaborate across technical and business teams. • Understanding of data privacy, security, governance, and compliance principles. Preferred Qualifications • Experience in financial services, wealth management, banking, healthcare, or other regulated industries. • Familiarity with CRM, portfolio accounting, financial reporting, or custodial data. • Experience building enterprise-scale analytics platforms using Microsoft Azure and Microsoft Fabric. • Exposure to modern data architecture patterns, including medallion architecture, data lakes, lakehouses, and enterprise data warehouses. • Experience working with AI-powered analytics, natural language querying, and enterprise data governance for AI adoption. What We Offer • Opportunity to work on modern data engineering and analytics transformation initiatives. • Exposure to enterprise-scale implementations across Microsoft Fabric, Power BI, Azure, and modern data platforms. • Opportunity to work with emerging AI technologies and help shape the future of enterprise analytics. • A collaborative, technology-driven environment with opportunities for continuous learning and professional growth. • The opportunity to take ownership, influence technical direction, and contribute to building Neutrino's Data & Analytics practice. About Neutrino Advisory Neutrino Advisory is a Digital Strategy, Advisory & Marketing Technology firm helping organizations navigate digital transformation through data, cloud, CRM, enterprise platforms, and applied AI. We combine business strategy with technology expertise to build scalable solutions that deliver measurable business outcomes. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform crucial job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Job Description Seeking a Computer Vision Engineer to detect altered and fabricated documents across 20 document types. You'll build Python-based checks for images and PDFs, measure how reliably they detect tampering, and give fraud reviewers clear evidence for each flag. Location: Remote (US), Sacramento or nearby preferred What you'll do Build checks for inconsistent fonts, text alignment, image edits, and anomalies in PDF structure or metadata. Create a labeled evaluation set using genuine documents, confirmed examples of tampering, and synthetic alterations. Test against emerging methods, including AI-generated documents. Tune detection thresholds with fraud reviewers. Measure precision, recall, and false positives at realistic fraud rates and across different image-quality levels. Run new checks in shadow mode before they affect review decisions, monitor performance after launch, and show reviewers which region or file detail triggered each flag. Qualifications 3+ years for mid-level or 6+ years for senior in applied computer vision, machine learning, or fraud detection, including at least one model deployed to production. Hands-on Python experience with OpenCV or scikit-image, plus PyTorch or TensorFlow. Experience inspecting images and PDFs programmatically, including rendering, metadata, and file structure. Experience evaluating models on imbalanced datasets, selecting thresholds, and explaining findings to nontechnical reviewers. Experience in document or image forensics, identity verification, or claims fraud is preferred. Familiarity with PyMuPDF, pikepdf, or ExifTool is a plus. Share your resume and one brief example of a detection model or check you personally buil t. Include what it detected and how you measured false positives.

Sr. Staff AI Engineer (Remote Eligible) 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. What You'll Do: 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, agents and multi-agent workflows, 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, PyTorch, and more. Invent and introduce state-of-the-art foundation model 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. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Capital One is open to hiring a Remote Employee for this opportunity. 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, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 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 AI systems Demonstrated ability to lead and mentor multiple engineering teams 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, CUDA, 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 Experience in building agentic AI systems and agentic workflows 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 Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $286,200 - $326,700 for Sr. Staff AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff 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).

AI Engineer 4 (LLM Gateway, FM Hosting) 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. What You'll Do: 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, agents and multi-agent workflows, 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, PyTorch, and more. Invent and introduce state-of-the-art foundation model 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. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation 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 enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer 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 4 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 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, 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 Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 4 (Vision model (VLM) customization experience) 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. What You'll Do: 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, agents and multi-agent workflows, 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, PyTorch, and more. Invent and introduce state-of-the-art foundation model 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. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation 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 enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer 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 4 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 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, 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 Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).