486 jobs found

Job DescriptionJob DescriptionJob Title: Artificial Intelligence Senior Associate Location: Dearborn, MI (local preferred) Duration: 12 Months (with potential for extension) Interview: Interview onsite in South Lyon/Novi, MI Candidate must be USC or GC. Do not apply for C2C. It will be a hybrid position. REVIEW JD MAKE SURE REQUIRED SKILLS (highlighted red) ARE ON THE RESUME. Will be onsite 4 days a week. Position Description: Employees in this job function are responsible for developing intelligent programs, cognitive applications and algorithms for data analysis and automation, leveraging various AI techniques such as deep learning, generative AI, natural language processing, image processing, cognitive automation, intelligent process automation, reinforcement learning, virtual assistants and specialized programming Key Responsibilities: Understand business requirements and develop AI algorithms, models and programs to solve complex problems, generate recommendations, extract patterns, make predictions, interpret sensor data (images, sound), orchestrate automation and enable self-service capabilities Perform large-scale experimentation and develop data driven applications that translate data into actionable intelligence Drive innovative applications of Artificial Intelligence tools and techniques such as deep learning, generative AI, natural language processing, image processing, cognitive automation, intelligent process automation, reinforcement learning, virtual assistants and specialized programming Research and optimize AI technologies to enhance efficiency and accuracy of data analysis and create more efficient automation Skills Required: Google Cloud Platform Experience Required: Bachelor's or Master's degree in Computer Science, Software Engineering, or related field (or equivalent practical experience). 3+ years building production software systems, including 1-2+ years on ML/AI or LLM-based applications. Proven experience designing and deploying multi-agent or multi-service architectures in production - not just notebooks or demos. As one 2026 hiring analysis puts it, the job is closer to distributed systems engineering with a probabilistic component than it is to ML research or prompt tweaking . Strong Python proficiency, including async/concurrent programming, and experience with backend frameworks (FastAPI, Flask). Hands-on experience with agent orchestration frameworks - LangGraph, CrewAI, LlamaIndex, or equivalent - for building stateful, multi-step, tool-using agent workflows. Practical experience building RAG pipelines: vector databases (pgvector, Pinecone, Weaviate, or Qdrant), embeddings, chunking strategies, and retrieval evaluation. Cloud deployment experience, ideally Google Cloud Platform (BigQuery, Cloud Run/GKE, Vertex AI, Pub/Sub) or equivalent AWS/Azure services. Strong SQL skills and experience with cloud data warehouses. Containerization and CI/CD experience (Docker, Kubernetes, GitHub Actions/Cloud Build). Experience building evaluation and observability pipelines for LLM/agent systems - offline eval sets, LLM-as-judge scoring, and tracing tools (LangSmith, Langfuse, OpenTelemetry, or equivalent) to track task success, latency, and cost. Understanding of LLM safety practices: guardrails, output validation, prompt-injection defense, and safe execution of AI-generated code/SQL (sandboxing, least privilege). Solid software engineering fundamentals: API design, testing, version control, security best practices. Experience Preferred: Experience with cost optimization and model routing - designing tiered pipelines that route between low-cost and high-capability models based on task complexity, and modeling per-conversation or per-task cost at scale. Experience deploying agentic systems with human-in-the-loop or multi-checkpoint validation workflows for high-reliability/high-stakes use cases. Experience with automotive, EV charging, IoT, or connected-vehicle telemetry data. Familiarity with Model Context Protocol (MCP) or similar standards for tool/data integration across agents. Prior experience in a startup or 0-to-1 product environment, comfortable with ambiguity and fast-evolving requirements. Education Required: Bachelor's Degree Education Preferred: Master's Degree Additional Information: Architect and deploy the production multi-agent orchestration layer (interpreter/orchestrator, NL-to-SQL agent, visualization agent, RCA/RAG agent, report composition agent, notification agent), using modern agent frameworks with state management and checkpointing rather than ad-hoc loops. Design and productionize RAG pipelines (chunking, embeddings, hybrid retrieval, reranking) grounded in approved schemas, engineering documentation, and historical issue records. Own BigQuery integration and enforce safe, least-privilege, validated execution of LLM-generated SQL. Build CI/CD, containerization, and infrastructure-as-code for deploying agent services on GCP (Cloud Run/GKE, Vertex AI). Implement evaluation pipelines and observability/tracing for every agent (golden datasets, LLM-as-judge scoring, regression alerts) so quality is measurable, not assumed. Implement guardrails, prompt-injection defenses, and human-in-the-loop approval checkpoints to ensure correctness and safety before any output triggers downstream action. Design cost/latency optimization strategies, including tiered model routing (cheap filter models vs. high-capability deep-dive models) and caching. Integrate validated outputs with operational systems (Salesforce ticketing, driver/site-manager notifications) and report export pipelines (PDF/HTML/spreadsheet). Collaborate with data scientists to productionize prototypes (anomaly detection, diagnostic agents) into scalable, monitored services. Establish versioning, testing, and safe rollout practices (canary/shadow deployments) for evolving agent logic.

Job DescriptionJob DescriptionJob Title: Artificial Intelligence Senior Associate Location: Dearborn, MI (local preferred) Duration: 12 Months (with potential for extension) Interview: Interview onsite in South Lyon/Novi, MI Candidate must be USC or GC. Do not apply for C2C. It will be a hybrid position. REVIEW JD MAKE SURE REQUIRED SKILLS (highlighted red) ARE ON THE RESUME. Will be onsite 4 days a week. Position Description: Employees in this job function are responsible for developing intelligent programs, cognitive applications and algorithms for data analysis and automation, leveraging various AI techniques such as deep learning, generative AI, natural language processing, image processing, cognitive automation, intelligent process automation, reinforcement learning, virtual assistants and specialized programming Key Responsibilities: Understand business requirements and develop AI algorithms, models and programs to solve complex problems, generate recommendations, extract patterns, make predictions, interpret sensor data (images, sound), orchestrate automation and enable self-service capabilities Perform large-scale experimentation and develop data driven applications that translate data into actionable intelligence Drive innovative applications of Artificial Intelligence tools and techniques such as deep learning, generative AI, natural language processing, image processing, cognitive automation, intelligent process automation, reinforcement learning, virtual assistants and specialized programming Research and optimize AI technologies to enhance efficiency and accuracy of data analysis and create more efficient automation Skills Required: Google Cloud Platform Experience Required: Bachelor's or Master's degree in Computer Science, Software Engineering, or related field (or equivalent practical experience). 3+ years building production software systems, including 1-2+ years on ML/AI or LLM-based applications. Proven experience designing and deploying multi-agent or multi-service architectures in production - not just notebooks or demos. As one 2026 hiring analysis puts it, the job is closer to distributed systems engineering with a probabilistic component than it is to ML research or prompt tweaking . Strong Python proficiency, including async/concurrent programming, and experience with backend frameworks (FastAPI, Flask). Hands-on experience with agent orchestration frameworks - LangGraph, CrewAI, LlamaIndex, or equivalent - for building stateful, multi-step, tool-using agent workflows. Practical experience building RAG pipelines: vector databases (pgvector, Pinecone, Weaviate, or Qdrant), embeddings, chunking strategies, and retrieval evaluation. Cloud deployment experience, ideally Google Cloud Platform (BigQuery, Cloud Run/GKE, Vertex AI, Pub/Sub) or equivalent AWS/Azure services. Strong SQL skills and experience with cloud data warehouses. Containerization and CI/CD experience (Docker, Kubernetes, GitHub Actions/Cloud Build). Experience building evaluation and observability pipelines for LLM/agent systems - offline eval sets, LLM-as-judge scoring, and tracing tools (LangSmith, Langfuse, OpenTelemetry, or equivalent) to track task success, latency, and cost. Understanding of LLM safety practices: guardrails, output validation, prompt-injection defense, and safe execution of AI-generated code/SQL (sandboxing, least privilege). Solid software engineering fundamentals: API design, testing, version control, security best practices. Experience Preferred: Experience with cost optimization and model routing - designing tiered pipelines that route between low-cost and high-capability models based on task complexity, and modeling per-conversation or per-task cost at scale. Experience deploying agentic systems with human-in-the-loop or multi-checkpoint validation workflows for high-reliability/high-stakes use cases. Experience with automotive, EV charging, IoT, or connected-vehicle telemetry data. Familiarity with Model Context Protocol (MCP) or similar standards for tool/data integration across agents. Prior experience in a startup or 0-to-1 product environment, comfortable with ambiguity and fast-evolving requirements. Education Required: Bachelor's Degree Education Preferred: Master's Degree Additional Information: Architect and deploy the production multi-agent orchestration layer (interpreter/orchestrator, NL-to-SQL agent, visualization agent, RCA/RAG agent, report composition agent, notification agent), using modern agent frameworks with state management and checkpointing rather than ad-hoc loops. Design and productionize RAG pipelines (chunking, embeddings, hybrid retrieval, reranking) grounded in approved schemas, engineering documentation, and historical issue records. Own BigQuery integration and enforce safe, least-privilege, validated execution of LLM-generated SQL. Build CI/CD, containerization, and infrastructure-as-code for deploying agent services on GCP (Cloud Run/GKE, Vertex AI). Implement evaluation pipelines and observability/tracing for every agent (golden datasets, LLM-as-judge scoring, regression alerts) so quality is measurable, not assumed. Implement guardrails, prompt-injection defenses, and human-in-the-loop approval checkpoints to ensure correctness and safety before any output triggers downstream action. Design cost/latency optimization strategies, including tiered model routing (cheap filter models vs. high-capability deep-dive models) and caching. Integrate validated outputs with operational systems (Salesforce ticketing, driver/site-manager notifications) and report export pipelines (PDF/HTML/spreadsheet). Collaborate with data scientists to productionize prototypes (anomaly detection, diagnostic agents) into scalable, monitored services. Establish versioning, testing, and safe rollout practices (canary/shadow deployments) for evolving agent logic.

Company / Location Information A.O. Smith is a global leader applying innovative technologies and energy-efficient solutions to products manufactured and marketed worldwide. The company is one of the world's leading manufacturers of residential and commercial water heating equipment and boilers, as well as a manufacturer of water treatment products for residential and light commercial applications. A. O. Smith is headquartered in Milwaukee, Wisconsin, with approximately 12,000 employees at operations in the United States, Canada, China, India, Mexico, the Netherlands, and the United Kingdom. Please Note : At this time, we are unable to provide visa sponsorship for this role. Candidates must be authorized to work in the United States without sponsorship now or in the future. Primary Function The SAP Supply Chain Senior Solutions Architect is responsible for defining, governing, and delivering enterprise supply chain technology solutions with a primary focus on SAP Materials Management (MM) and related business processes. This role serves as a strategic technology leader for Materials Management, Procurement, Vendor Management, Master Data, Logistics Execution, Inventory Management, and Warehouse Management capabilities. The position partners closely with business stakeholders, enterprise architects, vendors, and delivery teams to develop technology roadmaps, drive innovation, and ensure scalable, secure, and sustainable solutions that support business objectives. Role Specific Responsibilities Solution Architecture & Strategy Lead architecture and solution design activities for SAP MM and related Supply Chain processes. Define and maintain the long-term technology roadmap for Materials Management and supporting Supply Chain applications. Ensure alignment of solutions with enterprise architecture standards, cybersecurity requirements, and business strategy. Evaluate emerging technologies and recommend opportunities for modernization, automation, AI, and digital transformation. Business Process & Functional Leadership Provide subject matter expertise in: SAP Materials Management (MM) Procurement and Purchasing Vendor Management MM Master Data Governance Logistics Execution Inventory Management and Warehouse Management (WM/EWM) Collaborate with business leaders to identify process improvements and technology opportunities. Translate business requirements into scalable solution architectures and implementation roadmaps. Application Ownership & Integration Own the architecture, support strategy, and lifecycle management for SAP MM and associated Supply Chain solutions. Provide architectural oversight for integrations between SAP and non-SAP applications. Maintain accountability for business-critical integrated solutions, including vendor portals, external supply chain applications, and related platforms. Ensure system reliability, performance, scalability, and supportability. Governance & Delivery Lead architecture reviews and solution governance activities. Establish and enforce design standards, best practices, and development guidelines. Support project delivery teams through design reviews, risk assessments, and solution validation. Drive continuous improvement initiatives across Supply Chain Systems. Vendor & Stakeholder Management Manage strategic relationships with software vendors, implementation partners, and service providers. Provide technical leadership and guidance to analysts, developers, and project teams. Influence business and technology stakeholders through effective communication and strategic planning. Qualifications Required Qualifications Bachelor's degree in Information Technology, Supply Chain, Business, Engineering, or a related discipline. 7+ years of experience in SAP Supply Chain solution architecture, consulting, implementation, or enterprise application leadership. Deep expertise in SAP Materials Management (MM), Procurement, Vendor Management, Material Master, Logistics Execution, and Inventory Management Experience supporting SAP ECC and/or SAP S/4HANA environments including SAP Configuration, Functional Specifications, Testing, SAP Implementations, Material Master, Purchasing Demonstrated experience leading enterprise-scale solution design and architecture governance. Experience integrating SAP solutions with non-SAP applications and external platforms. Strong analytical, communication, leadership, and stakeholder management skills. Preferred Qualifications Experience leading large-scale ERP transformation or modernization initiatives. Knowledge of enterprise integration platforms, APIs, middleware, and cloud technologies. Experience with data governance, master data management, and reporting solutions. SAP certification(s) in MM, S/4HANA, or related Supply Chain disciplines. Experience with SAP WM and/or SAP EWM. Success Measures Delivery of scalable, secure, and supportable Supply Chain solutions. Alignment of technology investments with business strategy and roadmap objectives. Improved operational efficiency, process standardization, and user experience. Effective governance of SAP and integrated Supply Chain platforms. Strong vendor partnerships and successful execution of strategic initiatives, We Offer Competitive compensation package and comprehensive benefits plans which include medical and dental insurance, company-sponsored life insurance, retirement security savings plan, short- and long-term disability programs and tuition assistance. ADA Statement & EEO Statement In developing this job description care was taken to include all competencies needed to successfully perform in this position. However, for Americans with Disabilities Act (ADA) purposes, the essential functions of the job may or may not have been described for purposes of ADA reasonable accommodation. All reasonable accommodation requests will be reviewed and evaluated on a case-by-case basis. We consider all applicants for employment without regard to race, color, religion, gender, sexual orientation, national origin, age, disability, gender identity and expression, marital or military status. We also provide reasonable accommodations to qualified individuals with disabilities in accordance with the Americans with Disabilities Act and applicable state and local law.

Job DescriptionJob DescriptionDescription: About ACTIA ACTIA is a global leader in electronic and software solutions for commercial vehicles, transit, Bus & Coach, specialty vehicles, and off-highway markets. Our technologies enable intelligent vehicle architectures through multiplexing systems, electronic control units (ECUs), smart displays (SHMI), telematics, connectivity, and power management solutions. As the transportation industry transitions toward Software-Defined Vehicles (SDV), ACTIA is helping OEMs modernize vehicle architectures by integrating advanced software platforms, connected services, cloud technologies, and intelligent electronics into next-generation vehicles. Position Overview ACTIA is seeking a highly motivated Senior Application Engineer with a strong software and systems engineering background to support OEM customers in the design, integration, and deployment of complete vehicle electronic architectures. This role combines system architecture, software engineering, customer engagement, and vehicle integration. The successful candidate will work closely with OEMs to define and implement solutions built around ACTIA's portfolio of: Electronic Control Units (ECUs) Multiplexing Systems Smart Human Machine Interfaces (SHMI) Power Management Systems (MPSxx) Telematics and Connectivity Platforms Vehicle Networking and Diagnostics Solutions The ideal candidate understands both traditional distributed vehicle architectures and the industry's evolution toward Software-Defined Vehicles, centralized computing, connected services, and over-the-air software deployment. Experience within the Bus & Coach industry is highly preferred, while exposure to agriculture, construction, specialty, or heavy-duty vehicle applications is considered a strong asset. Key Responsibilities System Architecture & Solution Design Design complete electronic and software architectures using ACTIA hardware and software platforms. Define vehicle network architectures using CAN, J1939, CAN FD, Ethernet, and related communication technologies. Translate customer requirements into scalable and maintainable system architectures. Create architecture diagrams, interface definitions, functional specifications, and integration plans. Support vehicle-level integration activities including displays, body control systems, multiplexing, power management, diagnostics, and connectivity. Software-Defined Vehicle (SDV) Development Support customer migration from traditional distributed ECU designs toward Software-Defined Vehicle architectures. Define software-centric vehicle architectures supporting feature scalability and lifecycle management. Assist customers with OTA update strategies, remote diagnostics, fleet connectivity, and cloud integration. Support implementation of service-oriented architectures and connected vehicle ecosystems. Collaborate on strategies involving domain controllers, centralized computing, and zonal architectures. Software Development & Integration Develop and support software applications running on ACTIA platforms. Collaborate with software development teams throughout requirements, implementation, validation, and release activities. Support embedded Linux and application-level software development. Participate in software troubleshooting, debugging, and validation activities. Support test automation and software quality processes. Functional Safety & Compliance Support development activities compliant with ISO 26262 functional safety requirements. Contribute to safety analyses, system requirements allocation, verification planning, and validation activities. Collaborate with quality and engineering teams to ensure compliance with customer and regulatory requirements. Promote best practices for safety-critical development processes. CI/CD & DevOps Support modern software development workflows utilizing CI/CD methodologies. Contribute to build automation, testing automation, release management, and deployment strategies. Improve software quality through continuous integration and automated validation. Participate in code reviews and software quality initiatives. Support version control and release traceability processes. Customer-Facing Engineering Act as a primary technical interface between ACTIA and OEM customers. Lead technical workshops, architecture reviews, design discussions, and solution demonstrations. Support prototype development, vehicle commissioning, and launch activities. Provide technical guidance throughout project execution and customer development programs. Required QualificationsEducation Bachelor's Degree in: Computer Engineering Software Engineering Electrical Engineering Computer Science Automotive Engineering Related Engineering Discipline Experience 5+ years of experience in automotive, commercial vehicle, transportation, or embedded systems engineering. Proven experience designing complex electronic and software systems. Experience interfacing directly with customers and OEM engineering teams. Experience integrating hardware, embedded software, and vehicle networking technologies. Technical RequirementsVehicle Electronics & Networking CAN CAN FD SAE J1939 Ethernet Diagnostic protocols Vehicle multiplexing systems ECU integration Software Development C/C++ Python Scripting languages Linux environments Embedded software development Application software development Software Defined Vehicle (SDV) Understanding of Software-Defined Vehicle principles and architectures. Knowledge of centralized computing and domain controller architectures. Familiarity with OTA update strategies and software lifecycle management. Experience supporting connected vehicle and cloud-based software solutions. Understanding of software architecture principles for vehicle platforms. CI/CD & DevOps Experience with: Git Azure DevOps GitLab Jenkins Continuous Integration Continuous Deployment Automated testing frameworks Version control and release management Functional Safety & Quality Knowledge of: ISO 26262 Automotive SPICE (ASPICE) Requirements management Verification and validation processes Safety-critical software development Preferred Qualifications Experience in the Bus & Coach industry. Experience supporting transit agencies or commercial vehicle OEMs. Familiarity with ACTIA products and multiplexing architectures. Knowledge of vehicle electrical distribution systems and power management. Experience with telematics and connected fleet solutions. Familiarity with AUTOSAR Classic and/or Adaptive AUTOSAR. Knowledge of ISO 21434 automotive cybersecurity. Understanding of UNECE R155 and R156 requirements. Experience with cloud platforms, edge computing, and vehicle-to-cloud architectures. Experience with zonal architectures, domain controllers, and centralized vehicle computing. Exposure to electric vehicle (EV) or hybrid vehicle programs. Desired Characteristics Strong systems thinker with the ability to understand complete vehicle architectures. Customer-focused mindset and excellent communication skills. Ability to bridge software, hardware, networking, and vehicle integration disciplines. Strong analytical and problem-solving skills. Comfortable working in a fast-paced technical environment. Passion for emerging transportation technologies and Software-Defined Vehicles. What Success Looks Like Within your first year, you will: Lead architecture discussions with key OEM customers. Deliver complete vehicle solutions utilizing ACTIA ECUs, SHMIs, MPSxx power modules, and connectivity platforms. Support successful customer launches through integration, testing, and validation phases. Help establish modern CI/CD and software delivery practices for customer programs. Contribute to ISO 26262-compliant product development activities. Become a trusted technical advisor for vehicle architecture, software integration, and Software-Defined Vehicle initiatives. Why ACTIA? Join a company shaping the future of transportation through intelligent electronics, connected software platforms, and Software-Defined Vehicle technologies. You'll work directly with leading OEMs, influence next-generation vehicle architectures, and help transform how commercial vehicles are designed, connected, and maintained. Requirements: Minimum Qualifications and Education Bachelors or higher in EE, EET, ME, MET, CS or demonstrable equivalent Must have superior troubleshooting skills Experience in vehicle/vessel system architectures Experience with databus messaging structure & application; preferably CAN Experience with small signal analog electronic design Experience with Digital electronic design including microcontrollers . click apply for full job details

What you will do We are seeking a Manufacturing IT Platform Engineer with 8-10 years of traditional software development hands-on experience using AI-assisted development tools (e.g., Claude.ai, ChatGPT, GitHub Copilot). The role focuses on building productized, reusable capabilities for MoM/MES integration, manufacturing data platforms, and edge deployments, using containers and Kubernetes to deploy and support solutions in manufacturing plants. This role is ideal for an engineer who wants to build real systems used on the shop floor, leverage AI tools to accelerate development, and grow into a strong manufacturing platform contributor. How you will do it Design and develop services supporting MoM/MES use cases such as production events, quality data, and traceability. Build manufacturing data pipelines and APIs for real-time and near real time shop-floor data. Develop and maintain edge-deployed applications that interface with plant systems (MES, SCADA, historians, equipment data). Use AI development tools (Claude.ai, Copilot studio) for: Code generation and refactoring Test creation and debugging Documentation and design acceleration Configuration of the MOM/MES Containerize applications using Docker and deploy using Kubernetes (on prem or edge environments). Support plant deployments, validation, and basic production support. Collaborate with senior engineers and architects to improve reliability, scalability, and usability of the platform. What we look for Required 8-10 years of traditional software development experience in Manufacturing. 2-3 years of active experience using AI tools for software development. Strong coding skills in Python, Java, Node.js, or .NET. Experience building and consuming REST APIs and data services. Hands-on experience with Docker containers. Working knowledge of Kubernetes concepts (pods, deployments, services). Basic understanding of manufacturing or industrial systems (MES, shop-floor data, production systems). Preferred Exposure to MoM/MES, SCADA, Historian, or IoT systems. Experience with event-driven or streaming architectures (e.g., MQTT, pub/sub concepts). Any experience deploying applications to edge or on-prem environments. Familiarity with CI/CD pipelines and DevOps practices. Experience with manufacturing and shop-floor systems. Comfortable combining traditional engineering skills with AI-assisted development. Product-oriented mindset-focused on reusable, scalable solutions. Willingness to support plant users and learn from operational feedback. Curious, hands-on, and ownership driven. Meadowbrook - Lithium Ion Our Meadowbrook, Michigan plant produces lithium-ion batteries and runs a research lab. We began operations in 2010 and now employ more than 110 people and operate six days per week. We're mindful of the profound impact we have on our planet and are proud to operate in a LEED Gold Certified facility. Our employees are actively involved in the community and volunteer for a variety of local organizations. What you get: Medical, dental and vision care coverage and a 401(k) savings plan with company matching - all starting on date of hire Tuition reimbursement, perks, and discounts Parental and caregiver leave programs All the usual benefits such as paid time off, flexible spending, short-and long-term disability, basic life insurance, business travel insurance, and Employee Assistance Program Global market strength and worldwide market share leadership HQ location earns LEED certification for sustainability plus a full-service cafeteria and workout facility Clarios has been recognized as one of 2026's Most Ethical Companies by Ethisphere. This prestigious recognition marks the fourth consecutive year Clarios has received this distinction. Who we are: Clarios is the force behind the world's most recognizable car battery brands, powering vehicles from leading automakers like Ford, General Motors, Toyota, Honda, and Nissan. With 18,000 employees worldwide, we develop, manufacture, and distribute energy storage solutions while recovering, recycling, and reusing up to 99% of battery materials-setting the standard for sustainability in our industry. At Clarios, we're not just making batteries; we're shaping the future of sustainable transportation. Join our mission to innovate, push boundaries, and make a real impact. Discover your potential at Clarios-where your power meets endless possibilities. Veterans/Military Spouses: We value the leadership, adaptability, and technical expertise developed through military service. At Clarios, those capabilities thrive in an environment built on grit, ingenuity, and passion-where you can grow your career while helping to power progress worldwide. All qualified applicants will be considered without regard to protected characteristics. Equal Employment Opportunity: We recognize that people come with a wealth of experience and talent beyond just the technical requirements of a job. If your experience is close to what you see listed here, please apply. Diversity of experience and skills combined with passion is key to challenging the status quo. Therefore, we encourage people from all backgrounds to apply to our positions. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, status as a protected veteran or other protected characteristics protected by law. As a federal contractor, we are committed to not discriminating against any applicant or employee based on these protected statuses. We will also take affirmative action to ensure equal employment opportunities. Please let us know if you require accommodations during the interview process by emailing . We are an Equal Opportunity Employer and value diversity in our teams in terms of work experience, area of expertise, and all characteristics protected by laws in the countries where we operate. For more information on our commitment to sustainability, diversity, and equal opportunity, please read our latest report . We want you to know your rights because EEO is the law. A Note to Job Applicants: please be aware of scams being perpetrated through the Internet and social media platforms. Clarios will never require a job applicant to pay money as part of the application or hiring process. To All Recruitment Agencies: Clarios does not accept unsolicited agency resumes/CVs. Please do not forward resumes/CVs to our careers email addresses, Clarios employees or any other company location. Clarios is not responsible for any fees related to unsolicited resumes/CVs.

Amazon Web Services (AWS) seeks a Pan-Amazon MarTech/AdTech Architect to design and implement scalable, cloud-native marketing and advertising technology solutions across Amazon businesses. You will partner with product, marketing, and engineering teams to define architectures leveraging AWS analytics, data lakes, CDP concepts, identity/attribution, and real-time decisioning. Responsibilities include leading discovery and roadmap efforts, guiding migration to AWS, building reference architectures, and providing hands-on governance and best practices. You will influence C-level stakeholders, write technical documents, and mentor teams in a fast-paced, customer-obsessed environment. Responsibilities Architect scalable Mar Tech/Ad Tech solutions on AWS for Pan-Amazon initiatives Lead discovery, requirements gathering, and technical roadmaps with business and engineering stakeholders Design data architectures including data lakes, analytics, identity resolution, and attribution pipelines Define integration patterns with ad platforms, marketing platforms, and first-party data systems Create reference architectures, design docs, and best practices for customers and internal teams Guide migrations of existing Mar Tech/Ad Tech stacks to AWS services Provide technical leadership, code and design reviews, and governance for solution implementations Collaborate with C-level and senior leaders to align architecture with business strategy Mentor engineers and architects on cloud-native marketing and advertising architectures Ensure security, compliance, scalability, and cost optimization of proposed solutions Required Skills AWS architecture (EC2, S3, Lambda, ECS/EKS) Data lake and data warehouse design (S3, Redshift, Lake Formation) Streaming and real-time processing (Kinesis, Kafka) Identity resolution, customer data platforms (CDP), and attribution modeling SQL and data modeling for analytics API and microservices architecture Security, compliance, and governance on AWSMar Tech/Ad Tech platforms and integrations Solution architecture and technical leadership Technical documentation and stakeholder communication

Qualcomm seeks a Sr. Engineer, AI Platforms to design, build, and optimize large scale AI platforms that power next generation wireless, 5G, and connected devices. You will architect end to end AI/ML pipelines, integrate models into Qualcomm chipsets and cloud/edge environments, and ensure high performance, reliability, and security. Partner with silicon, software, and product teams to deliver scalable inference services, tools, and SDKs. Responsibilities include model deployment, performance tuning on heterogeneous hardware, MLOps automation, monitoring, and contributing to technical strategy in a fast paced, innovation driven culture. Responsibilities Architect and develop large-scale AI/ML platforms and services for wireless and 5 G applications Design and implement end-to-end AI pipelines from data ingestion to deployment and monitoring Optimize AI workloads for Qualcomm chipsets, heterogeneous compute, and edge/cloud environments Collaborate with silicon, software, and product teams to integrate AI into commercial products Implement MLOps practices including CI/CD, model versioning, and automated deployment Monitor and improve platform performance, reliability, scalability, and security Contribute to technical strategy, platform roadmap, and best practices for AI engineering Create tools, SDKs, and APIs to enable internal teams and external partners Troubleshoot complex production issues across distributed systems and accelerators Document architectures, designs, and operational runbooks Required Skills Python C++Machine learning frameworks (Tensor Flow, Py Torch, ONNX) MLOps and CI/CD for MLKubernetes and containerization Distributed systems and microservices Cloud platforms (AWS, Azure, or GCP) GPU/accelerator optimization Data pipelines and ETLMonitoring, observability, and performance tuning

Sr. Staff 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. 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 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. 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 Richmond, VA: $286,200 - $326,700 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 (AI Foundations, LLM Customization and Finetuning) 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 Francisco, CA: $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).

Sr. Staff 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. 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 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. 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 Richmond, VA: $286,200 - $326,700 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).

Sr. Staff 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. 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 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. 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 Richmond, VA: $286,200 - $326,700 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).

Summary The Senior Data Integration Engineer is responsible for the design, development, and operation of the data integration and ingestion processes that deliver partner and internal data into our analytics environment. The role owns the flow of data from source acquisition through the curated data warehouse tables consumed by reporting platforms, operational systems, and business analysts. This is a senior, hands-on engineering position spanning the full integration lifecycle: acquiring data from a wide range of external partner and internal systems, validating and conditioning that data on arrival, transforming it into the structures that support analysis and operations, and operating those processes reliably in production. The role is concerned equally with building new integrations and with the continued performance, accuracy, and timeliness of those already in service. A central objective of the position is to advance reusable, well-instrumented integration patterns that shorten the time required to onboard new data sources and that improve the reliability and transparency of data delivery to the business. The Senior Data Integration Engineer will also contribute substantially to the planned modernization of our data platform, evaluating and recommending tooling, architecture, and migration approach for leadership consideration. The role sets technical direction and development standards for data integration work and collaborates closely with data architects, business analysts, stakeholders across the organization, and the technical contacts of our external data partners. Essential Duties and Responsibilities This list of duties and responsibilities is not all inclusive and may be expanded to include other duties and responsibilities as management may deem necessary from time to time. Design, develop, and maintain data integration processes that acquire data from partner and internal sources, including flat file transfers over SFTP, REST API endpoints, and direct database connections. Develop reusable, configuration-driven ingestion patterns that reduce the effort and elapsed time required to onboard new partner data feeds. Develop and maintain the T-SQL transformation logic that carries data from landing and staging layers through to the curated warehouse tables supporting reporting, operational systems, and analyst queries. Design ingestion processes to be idempotent and safely re-runnable, incorporating automated retry and restart behavior for failed executions. Implement automated validation and quarantine processes so that records failing business-defined quality rules are isolated, reported, and prevented from reaching downstream consumers. Implement data quality rules defined by the business, including schema validation, reconciliation, row count and threshold checks, and anomaly detection. Establish monitoring, logging, and alerting for pipeline execution state, data freshness, and load completion, and automate the communication of ingestion status to stakeholders. Diagnose and resolve production data incidents, determine root cause, coordinate remediation, and document preventive measures through runbooks and post-incident review. Contribute to dimensional data model design in collaboration with the data architect and senior team members. Establish and maintain version control, code review, and repeatable deployment practices for database and pipeline code. Define and uphold development standards for data integration work through code review and technical guidance. Evaluate and recommend tooling, architecture, and sequencing for the platform modernization effort for leadership consideration. Migrate established integration workflows to modernized patterns incrementally and without disruption to production operations. Maintain documentation of data feeds, dependencies, lineage, ownership, and escalation paths. Perform all work involving protected health information in accordance with HIPAA requirements, including least-privilege access, secure transmission and storage of partner data, and the exclusion of PHI from logs and non-production environments. Coordinate with partner technical contacts, as needed, to resolve file format, schema, and connectivity questions. Provide occasional off-hours support for critical data load failures or production support rotations as needed to support timely response to critical data issues. Support AI and machine learning initiatives by maintaining reliable, secure, and well-governed data pipelines and datasets used for model development, testing, deployment, monitoring, and ongoing performance evaluation. Maintain confidentiality of information processed & follow company policies and procedures. Qualifications Requires six (6) or more years of professional data engineering, data operations, data platform operations, or related experience. Bachelor's degree in Computer Science, Engineering, Information Systems, or related field, or equivalent professional experience preferred. Experience leading teams and developing supervisory staff preferred. 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, skill, and/or ability required. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. Other qualifications include: Advanced T-SQL development skills, including: Set-based rewriting of row-by-row and cursor-based logic. MERGE, upsert, and slowly changing dimension load patterns. Window functions and complex analytic queries. Execution plan analysis, index strategy, statistics management, and resolution of performance issues such as parameter sniffing. Transaction management and structured error handling within stored procedures, including correct rollback behavior on partial failure. Demonstrated proficiency in Python for data engineering applications, including API-based data acquisition, file parsing and format handling, data validation, and the development of packaged, scheduled jobs. Familiarity with common data libraries such as requests and pandas is expected. Demonstrated experience acquiring and integrating data from heterogeneous sources, including delimited, fixed-width, JSON, and XML file formats; REST APIs requiring authentication, pagination, and rate-limit handling; and direct database connectivity. Proficiency with Git and collaborative development workflows, including branching, pull requests, and code review. A code-first development approach, with integration logic authored and maintained in T-SQL and Python under source control. Ability to analyze pipeline and query performance and to improve the reliability, scalability, and cost efficiency of data workloads. Strong written communication skills, with the ability to produce runbooks, technical documentation, and incident reports, and to convey the business impact of technical issues to non-technical stakeholders. Strong problem-solving skills, attention to detail, and demonstrated ownership of production systems. Experience with Microsoft Azure data services such as Azure Data Factory or Microsoft Fabric, or comparable cloud orchestration platforms. Experience migrating on-premises SQL Server integration workloads to a cloud platform. Experience with dimensional modeling and data warehouse design. Experience designing and rationalizing SQL Server Agent job dependencies and scheduling. Experience establishing version control, code review, and repeatable deployment practices for database code. Experience implementing CI/CD pipelines for database projects. Experience handling protected health information under HIPAA, or comparably regulated data under an equivalent framework preferred. Experience with healthcare or pharmacy data, including claims, eligibility, prescription, or delivery data preferred. Familiarity with data governance, metadata management, and data lineage practices. Physical Demands The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. (The phrases "occasionally," "regularly," and "frequently" correspond to the following definitions: "Occasionally" means up to 1/3 of working time, "regularly" means between 1/3 and 2/3 of working time, and "frequently" means 2/3 and more working time.) While performing the duties of this job, the employee is frequently required to sit; talk or hear; and use hands to handle, or touch objects or controls. The employee is regularly required to stand and walk. On occasion the incumbent may be required to stoop, bend or reach above the shoulders. The employee would rarely need to lift up to 25 pounds. Specific vision abilities required by this job include close vision, distance vision, color vision, peripheral vision, depth perception, and ability to adjust focus. Work Environment The position is a hybrid position with 2 - 3 days office presence in Milwaukee, WI required. The colleague may perform work-related travel on rare occasions (less than 10%) with an emphasis on travel for impact. . click apply for full job details

AI Engineer 4 (AI Foundations, LLM Customization and Finetuning) 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 Francisco, CA: $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).

Job DescriptionJob Description Location: Hybrid, 3 days in office / 2 remote open to candidates based near New York City, NY; Boston, MA; Chicago, IL; Louisville, KY; Phoenix, AZ; Urbandale, IA; or London, UK Compensation: $131,000-$200,000 base salary Step into a techno-functional leadership role owning the evolution of a cloud-based finance and ERP platform, bridging business, finance, and technology for a global professional services firm. What You'll Own - Collaborate with business, finance, and technical teams to translate requirements into clear user stories and acceptance criteria - Design end-to-end ERP solutions, leading fit-gap analysis and advising on functionality, cost, and risk - Define and oversee custom architectures including API and data integrations - Serve as the go-to subject-matter expert for the finance platform, monitoring performance and implementing enhancements - Drive continuous improvement, UAT, and change management, fostering adoption through training and documentation - Provide advanced technical support while maintaining strong documentation and IT controls compliance What You'll Bring - Degree in Computer Science or a related field - Hands-on experience with an enterprise finance/ERP system, ideally on the Salesforce platform - Proven expertise in accounting processes including Time Entry, Revenue Recognition, WIP, and backlog reporting - Experience delivering technical solutions in Agile (Scrum/SAFe) environments and partnering with business stakeholders - Familiarity with tools such as ServiceNow, Jira, or Azure DevOps - A genuine techno-functional mindset: hands-on technically while communicating clearly with senior stakeholders Nice to Have - Hands-on experience with Certinia PSA or Accounting (ERP) solutions - Deep Salesforce-platform finance/ERP module knowledge (billing, multi-currency, project economics) - Experience coaching or mentoring admin or analyst teams If you love bridging finance and technology and can move from the technical weeds to the boardroom, this is a strong next step.

Job DescriptionJob Description Location: Hybrid, 3 days in office / 2 remote open to candidates based near New York City, NY; Boston, MA; Chicago, IL; Louisville, KY; Phoenix, AZ; Urbandale, IA; or London, UK Compensation: $131,000-$200,000 base salary Step into a techno-functional leadership role owning the evolution of a cloud-based finance and ERP platform, bridging business, finance, and technology for a global professional services firm. What You'll Own - Collaborate with business, finance, and technical teams to translate requirements into clear user stories and acceptance criteria - Design end-to-end ERP solutions, leading fit-gap analysis and advising on functionality, cost, and risk - Define and oversee custom architectures including API and data integrations - Serve as the go-to subject-matter expert for the finance platform, monitoring performance and implementing enhancements - Drive continuous improvement, UAT, and change management, fostering adoption through training and documentation - Provide advanced technical support while maintaining strong documentation and IT controls compliance What You'll Bring - Degree in Computer Science or a related field - Hands-on experience with an enterprise finance/ERP system, ideally on the Salesforce platform - Proven expertise in accounting processes including Time Entry, Revenue Recognition, WIP, and backlog reporting - Experience delivering technical solutions in Agile (Scrum/SAFe) environments and partnering with business stakeholders - Familiarity with tools such as ServiceNow, Jira, or Azure DevOps - A genuine techno-functional mindset: hands-on technically while communicating clearly with senior stakeholders Nice to Have - Hands-on experience with Certinia PSA or Accounting (ERP) solutions - Deep Salesforce-platform finance/ERP module knowledge (billing, multi-currency, project economics) - Experience coaching or mentoring admin or analyst teams If you love bridging finance and technology and can move from the technical weeds to the boardroom, this is a strong next step.

Job DescriptionJob Description Location: Hybrid, 3 days in office / 2 remote open to candidates based near New York City, NY; Boston, MA; Chicago, IL; Louisville, KY; Phoenix, AZ; Urbandale, IA; or London, UK Compensation: $131,000-$200,000 base salary Step into a techno-functional leadership role owning the evolution of a cloud-based finance and ERP platform, bridging business, finance, and technology for a global professional services firm. What You'll Own - Collaborate with business, finance, and technical teams to translate requirements into clear user stories and acceptance criteria - Design end-to-end ERP solutions, leading fit-gap analysis and advising on functionality, cost, and risk - Define and oversee custom architectures including API and data integrations - Serve as the go-to subject-matter expert for the finance platform, monitoring performance and implementing enhancements - Drive continuous improvement, UAT, and change management, fostering adoption through training and documentation - Provide advanced technical support while maintaining strong documentation and IT controls compliance What You'll Bring - Degree in Computer Science or a related field - Hands-on experience with an enterprise finance/ERP system, ideally on the Salesforce platform - Proven expertise in accounting processes including Time Entry, Revenue Recognition, WIP, and backlog reporting - Experience delivering technical solutions in Agile (Scrum/SAFe) environments and partnering with business stakeholders - Familiarity with tools such as ServiceNow, Jira, or Azure DevOps - A genuine techno-functional mindset: hands-on technically while communicating clearly with senior stakeholders Nice to Have - Hands-on experience with Certinia PSA or Accounting (ERP) solutions - Deep Salesforce-platform finance/ERP module knowledge (billing, multi-currency, project economics) - Experience coaching or mentoring admin or analyst teams If you love bridging finance and technology and can move from the technical weeds to the boardroom, this is a strong next step.