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City/State Virginia Beach, VA Work Shift Multiple shifts available Overview: Sentara is hiring a Senior MLOps & Generative AI Engineer! This position is fully remote! Candidates must reside in one of the following states: Alabama, Delaware, Florida, Georgia, Idaho, Indiana, Kansas, Louisiana, Maine, Maryland, Minnesota, Nebraska, Nevada, New Hampshire, North Dakota, Ohio, Oklahoma, Pennsylvania, South Carolina, South Dakota, Tennessee, Texas, Utah, Washington, West Virginia, Wisconsin, or Wyoming. Overview We are seeking a highly skilled and experienced Senior MLOps & Generative AI Engineer to join our growing AI organization and help advance current and future initiatives applying machine learning, deep learning, NLP, and Generative AI technologies to improve healthcare outcomes and operational excellence. This role combines two critical focus areas: MLOps Engineering - building and scaling enterprise-grade ML infrastructure, deployment pipelines, observability, governance, and automation capabilities. Generative AI Engineering - designing, architecting, deploying, and optimizing secure, production-ready GenAI applications and platforms leveraging LLMs, RAG architectures, vector databases, prompt orchestration, and AI evaluation frameworks. As a Senior Engineer, you will partner closely with AI Scientists, Data Engineers, Software Engineers, Architects, and Product teams to operationalize AI/ML and Generative AI solutions at enterprise scale. You will play a key role in shaping the organization's AI platform strategy, driving best practices, and delivering scalable, secure, and reliable AI systems in production healthcare environments. Key Responsibilities MLOps Engineering Responsibilities Design, build, and maintain scalable ML infrastructure and pipelines supporting model training, deployment, monitoring, governance, and lifecycle management. Develop and optimize CI/CD pipelines for machine learning and AI workloads across development, staging, and production environments. Build reusable ML platform capabilities including feature stores, model registries, experimentation frameworks, artifact management, and deployment automation. Implement scalable orchestration and workflow solutions for batch and real-time ML inference workloads. Create robust monitoring systems to measure model performance, detect model drift, monitor data quality, and ensure production reliability. Develop automation tools and self-service capabilities to improve the efficiency, scalability, and reliability of MLOps processes. Collaborate with Data Scientists and Software Engineers to streamline the ML lifecycle from experimentation through enterprise production deployment. Apply software engineering best practices to AI/ML systems including testing, observability, resiliency, security, versioning, and infrastructure-as-code. Identify gaps and improvement opportunities within the organization's ML platform ecosystem and architect scalable solutions to address them. Support enterprise AI governance, compliance, auditability, and model risk management requirements. Ensure platform scalability, reliability, security, and operational excellence across AI/ML systems. Generative AI Engineering Responsibilities Lead the architecture, design, and deployment of enterprise Generative AI solutions leveraging LLMs, foundation models, and agentic AI systems. Design and implement Retrieval-Augmented Generation (RAG) pipelines using vector databases, embeddings, semantic search, reranking, and retrieval optimization strategies. Build scalable LLM orchestration frameworks using technologies such as LangChain, LlamaIndex, Semantic Kernel, or equivalent frameworks. Develop advanced prompt engineering strategies, prompt chaining, context management, and agent workflows to improve LLM accuracy and reliability. Evaluate and implement fine-tuning, parameter-efficient tuning, and prompt-based optimization approaches for domain-specific use cases. Build AI evaluation and benchmarking frameworks to measure hallucination rates, response quality, grounding accuracy, toxicity, bias, latency, and business performance metrics. Implement AI safety guardrails, governance controls, content filtering, and responsible AI practices for enterprise healthcare environments. Design scalable GenAI APIs and microservices supporting high-throughput enterprise AI applications. Optimize GenAI systems for cost, latency, throughput, and inference performance across cloud and hybrid environments. Integrate enterprise data sources, healthcare systems, and knowledge repositories into secure GenAI workflows. Research and evaluate emerging GenAI technologies, open-source frameworks, and foundation models to drive innovation and continuous improvement. Develop architecture diagrams, technical roadmaps, implementation strategies, and executive-level documentation for enterprise AI initiatives. Collaborate with cybersecurity, compliance, and infrastructure teams to ensure secure and compliant deployment of GenAI solutions involving PHI and sensitive healthcare data. Contribute to the development of AI platform standards, reusable GenAI accelerators, templates, and engineering best practices. Required Qualifications 5+ years of experience building and deploying production software, ML systems, or AI platforms. 1+ years of hands-on experience building production Generative AI or LLM-based applications. Strong programming skills in Python and experience with software engineering best practices. Experience with major deep learning and LLM frameworks such as PyTorch, Hugging Face Transformers, TensorFlow, or equivalent. Hands-on experience implementing RAG architectures, vector search, embeddings, prompt engineering, and LLM orchestration frameworks. Experience with vector databases such as Pinecone, Weaviate, Chroma, FAISS, Milvus, or equivalent technologies. Experience deploying AI/ML systems in cloud environments including AWS, Azure, or GCP. Strong understanding of APIs, distributed systems, microservices, and scalable backend architectures. Experience with Kubernetes, containerization, orchestration, and cloud-native infrastructure. Experience implementing CI/CD pipelines, infrastructure automation, and MLOps best practices. Experience building monitoring, observability, and alerting solutions for ML and AI systems. Strong understanding of AI/ML lifecycle management, governance, model versioning, and production operations. Experience designing secure, scalable, production-ready AI platforms and services. Strong communication and collaboration skills with the ability to work across technical and business teams. Preferred Qualifications Previous experience implementing Generative AI and MLOps solutions within healthcare environments. Experience working with EPIC or healthcare interoperability platforms. Understanding of HIPAA, PHI handling, healthcare compliance, and responsible AI practices. Experience with AI governance frameworks, LLM evaluation methodologies, and AI safety tooling. Experience with GPU infrastructure optimization and scalable inference architectures. Familiarity with multi-agent AI systems and autonomous workflows. Experience with event-driven architectures, streaming pipelines, and real-time inference systems. Exposure to model fine-tuning techniques including LoRA, PEFT, RLHF, or domain adaptation strategies. Experience with enterprise AI platform architecture and internal developer platforms. Prior experience mentoring engineers and leading technical initiatives. Education 5+ years of relevant experience with a degree (Required) or 7+ years of relevant experience without a degree (Required) Experience in lieu of Bachelor's Degree. Certification/Licensure No specific certification or licensure requirements Experience 5 to 7 years of relevant experience We provide market-competitive compensation packages, inclusive of base pay, incentives, and benefits. The base pay rate for Full Time employment is: $91,416.00 - $152,380.80. Additional compensation may be available for this role such as shift differentials, standby/on-call, overtime, premiums, extra shift incentives, or bonus opportunities. Benefits: Caring For Your Family and Your Career • Medical, Dental, Vision plans • Adoption, Fertility and Surrogacy Reimbursement up to $10,000 • Paid Time Off and Sick Leave • Paid Parental & Family Caregiver Leave • Emergency Backup Care • Long-Term, Short-Term Disability, and Critical Illness plans • Life Insurance • 401k/403B with Employer Match • Tuition Assistance - $5,250/year and discounted educational opportunities through Guild Education • Student Debt Pay Down - $10,000 • Reimbursement for certifications and free access to complete CEUs and professional development •Pet Insurance •Legal Resources Plan . click apply for full job details

Lead AI Engineer At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 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, or Java Preferred Qualifications: 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, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for Lead AI Engineer New York, NY: $215,200 - $245,600 for Lead AI Engineer Richmond, VA: $179,400 - $204,700 for Lead AI Engineer San Jose, CA: $215,200 - $245,600 for Lead 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).

Job Description AI Engineer Data Science & AI Engineering Full-Time Hybrid (3 days/per week in office) The Opportunity MassMutual's AI & Data Science team is seeking a skilled AI Engineer to join our high-performing, cross-functional team. In this role, you will own the design, development, and delivery of AI solutions that address complex, high-value business problems across the enterprise. You'll apply machine learning, generative and agentic AI, and LLM-based techniques to real-world challenges, working independently to scope problems, build and evaluate solutions, and bring them into production. At this level, you are expected to take full ownership of defined initiatives with minimal supervision, driving quality and performance from development through deployment. The Team This is a unique opportunity to work alongside experts in applied AI, statistics, and computer science. The team operates at the intersection of cutting-edge research and enterprise delivery, building AI solutions that shape the future of MassMutual and the life insurance industry at large. We partner closely with technology and business stakeholders across the organization, and we invest in growth through a culture of peer learning, candid feedback, and shared technical standards. The team is defined by a shared commitment to scientific and engineering excellence, meaningful work, and the kind of collaboration that makes challenging problems tractable. The Impact Design, build, and deliver end-to-end AI/ML solutions for defined business use cases, using LLMs, deep learning, agentic AI, and probabilistic modeling, with ownership of quality and performance from development through deployment. Frame and scope AI problems independently, defining success metrics and evaluation criteria in collaboration with stakeholders before and during solution development. Design and conduct rigorous evaluations of AI system performance, including experimentation, benchmarking across models, and quantitative analysis, to validate approaches and support sound technical decisions. Build rapid prototypes to test AI approaches and advance validated solutions into production-grade applications (e.g., intelligent interfaces, dashboards, automated pipelines). Apply best practices in AI development, responsible AI deployment, and production engineering, contributing to team-wide standards and reusable frameworks. Communicate findings and recommendations clearly to technical peers and non-technical stakeholders, translating quantitative results into actionable insights. Contribute to team knowledge and development, including peer feedback, documentation, and knowledge sharing with less experienced colleagues. The Minimum Qualifications 4+ years of experience in data science, machine learning, or AI engineering, with a track record of delivering AI/ML solutions independently and at scale. 4+ years of experience across the following areas: Machine learning, statistics, NLP, and LLMs, including generative AI, agentic architectures, prompt engineering, and evaluation of LLM performance across foundation models. Building and deploying production AI systems, including model integration, API development, and cloud-based infrastructure. Python programming, with the ability to write clean, well-tested, production-quality code. Bachelor's degree in Computer Science, Statistics, Applied Mathematics, Electrical Engineering, Physics, or a related quantitative field. The Ideal Qualifications Experience with agentic AI frameworks and tooling, such as Bedrock AgentCore, AWS Strands, Azure, and MCP/A2A protocols. Breadth across AI and data science methods, including classical ML, causal inference, optimization, and Bayesian approaches, with comfort working across techniques as problems demand. Proficiency in SQL and database design; familiarity with cloud-native data platforms, vector databases, and semantic search. Master's degree or equivalent depth demonstrated through research, applied projects, or prior work. Candidates with a Master's may be considered with fewer years of professional experience. Applied research credentials, such as published work, significant open-source contributions, or a demonstrated record of scientific rigor in industry. Clear and effective communication skills, with the ability to explain technical concepts and present findings to both technical and non-technical audiences. What to Expect as Part of MassMutual and the Team Regular meetings with the AI & Data Science team Focused one-on-one meetings with your manager Networking opportunities including access to Asian, Hispanic/Latinx, African American, women, LGBTQIA+, veteran and disability-focused Business Resource Groups Access to learning content on Degreed and other informational platforms Your ethics and integrity will be valued by a company with a strong and stable ethical business with industry leading pay and benefits MassMutual is an equal employment opportunity employer. We welcome all persons to apply. If you need an accommodation to complete the application process, please contact us and share the specifics of the assistance you need. California residents: For detailed information about your rights under the California Consumer Privacy Act (CCPA), please visit our California Consumer Privacy Act Disclosures page.

Job Description AI Engineer Data Science & AI Engineering Full-Time Hybrid (3 days/per week in office) The Opportunity MassMutual's AI & Data Science team is seeking a skilled AI Engineer to join our high-performing, cross-functional team. In this role, you will own the design, development, and delivery of AI solutions that address complex, high-value business problems across the enterprise. You'll apply machine learning, generative and agentic AI, and LLM-based techniques to real-world challenges, working independently to scope problems, build and evaluate solutions, and bring them into production. At this level, you are expected to take full ownership of defined initiatives with minimal supervision, driving quality and performance from development through deployment. The Team This is a unique opportunity to work alongside experts in applied AI, statistics, and computer science. The team operates at the intersection of cutting-edge research and enterprise delivery, building AI solutions that shape the future of MassMutual and the life insurance industry at large. We partner closely with technology and business stakeholders across the organization, and we invest in growth through a culture of peer learning, candid feedback, and shared technical standards. The team is defined by a shared commitment to scientific and engineering excellence, meaningful work, and the kind of collaboration that makes challenging problems tractable. The Impact Design, build, and deliver end-to-end AI/ML solutions for defined business use cases, using LLMs, deep learning, agentic AI, and probabilistic modeling, with ownership of quality and performance from development through deployment. Frame and scope AI problems independently, defining success metrics and evaluation criteria in collaboration with stakeholders before and during solution development. Design and conduct rigorous evaluations of AI system performance, including experimentation, benchmarking across models, and quantitative analysis, to validate approaches and support sound technical decisions. Build rapid prototypes to test AI approaches and advance validated solutions into production-grade applications (e.g., intelligent interfaces, dashboards, automated pipelines). Apply best practices in AI development, responsible AI deployment, and production engineering, contributing to team-wide standards and reusable frameworks. Communicate findings and recommendations clearly to technical peers and non-technical stakeholders, translating quantitative results into actionable insights. Contribute to team knowledge and development, including peer feedback, documentation, and knowledge sharing with less experienced colleagues. The Minimum Qualifications 4+ years of experience in data science, machine learning, or AI engineering, with a track record of delivering AI/ML solutions independently and at scale. 4+ years of experience across the following areas: Machine learning, statistics, NLP, and LLMs, including generative AI, agentic architectures, prompt engineering, and evaluation of LLM performance across foundation models. Building and deploying production AI systems, including model integration, API development, and cloud-based infrastructure. Python programming, with the ability to write clean, well-tested, production-quality code. Bachelor's degree in Computer Science, Statistics, Applied Mathematics, Electrical Engineering, Physics, or a related quantitative field. The Ideal Qualifications Experience with agentic AI frameworks and tooling, such as Bedrock AgentCore, AWS Strands, Azure, and MCP/A2A protocols. Breadth across AI and data science methods, including classical ML, causal inference, optimization, and Bayesian approaches, with comfort working across techniques as problems demand. Proficiency in SQL and database design; familiarity with cloud-native data platforms, vector databases, and semantic search. Master's degree or equivalent depth demonstrated through research, applied projects, or prior work. Candidates with a Master's may be considered with fewer years of professional experience. Applied research credentials, such as published work, significant open-source contributions, or a demonstrated record of scientific rigor in industry. Clear and effective communication skills, with the ability to explain technical concepts and present findings to both technical and non-technical audiences. What to Expect as Part of MassMutual and the Team Regular meetings with the AI & Data Science team Focused one-on-one meetings with your manager Networking opportunities including access to Asian, Hispanic/Latinx, African American, women, LGBTQIA+, veteran and disability-focused Business Resource Groups Access to learning content on Degreed and other informational platforms Your ethics and integrity will be valued by a company with a strong and stable ethical business with industry leading pay and benefits MassMutual is an equal employment opportunity employer. We welcome all persons to apply. If you need an accommodation to complete the application process, please contact us and share the specifics of the assistance you need. California residents: For detailed information about your rights under the California Consumer Privacy Act (CCPA), please visit our California Consumer Privacy Act Disclosures page.

The Opportunity MassMutual's AI & Data Science team is seeking an impact-driven Lead AI Engineer to join our high-performing, cross-functional team. In this role, you will lead the design, deployment, and production scaling of advanced AI solutions that solve complex, high-value problems across the enterprise. You'll architect and deliver generative AI, agentic AI, and LLM-based systems by applying rigorous scientific methods, writing high-quality production code, and communicating results to senior leadership. The Team This is a unique opportunity to work alongside experts in applied AI, statistics, and computer science. The team operates at the intersection of cutting-edge research and enterprise delivery, building AI solutions that shape the future of MassMutual and the life insurance industry at large. We partner closely with technology and business stakeholders across the organization, and we invest in growth through a culture of peer learning, candid feedback, and shared technical standards. This team is defined by a shared commitment to scientific and engineering excellence, meaningful work, and the kind of collaboration that makes challenging problems tractable. The Impact Architect, build, and lead end-to-end AI solutions supporting a range of enterprise use cases-from ideation through production deployment and monitoring-using LLMs, agentic AI, machine learning, and probabilistic modeling, with accountability for reliability, performance, and maintainability. Design and conduct rigorous evaluations of AI system performance, including experimentation, benchmarking across foundation models, and quantitative analysis, to validate approaches and inform technical decisions. Drive innovation by identifying emerging technologies, translating cutting-edge research into practical applications, and establishing team-wide best practices in AI development and responsible AI deployment. Build rapid prototypes to test and validate AI approaches and deliver production-grade AI-powered applications (e.g., intelligent interfaces, dashboards, automated workflows) when solutions prove viable. Collaborate with engineering teams to build robust, production-grade AI pipelines and APIs that integrate into the broader enterprise technology ecosystem. Influence senior leadership by aligning AI initiatives with enterprise strategy and communicating complex technical concepts and findings in clear, actionable terms. Mentor and develop junior talent, fostering a culture of technical excellence, scientific rigor, and continuous learning across the team. The Minimum Qualifications 7+ years of experience in data science, machine learning, or AI engineering, with a track record of delivering impactful AI/ML solutions at scale. Deep expertise in machine learning, statistics, NLP, and LLMs, including generative AI, agentic architectures, prompt engineering, and LLM evaluation across a variety of foundation models and benchmarks. Demonstrated ability to build, deploy, and scale production AI systems from architecture planning through orchestration, monitoring, and end-user delivery. Strong programming skills in Python, with the ability to write clean, well-tested, production-quality code, including familiarity with Docker, Kubernetes, and other orchestration and deployment frameworks. M.S. or Ph.D. in Computer Science, Statistics, Applied Mathematics, Electrical Engineering, Physics, or a related quantitative field. The Ideal Qualifications Familiarity with agentic AI tooling ecosystems, such as Bedrock AgentCore, AWS Strands, Azure, and MCP/A2A protocols. Experience developing and evaluating AI systems in a regulated industry, with a strong understanding of compliance and privacy standards. Breadth across AI and data science methods-including classical ML, causal inference, optimization, and Bayesian approaches-with comfort moving across techniques as problems demand. Proficiency in SQL and database design; familiarity with cloud-native data platforms, vector databases, and semantic search. Exceptional ability to translate complex AI concepts and quantitative findings into clear insights for non-technical stakeholders and senior leadership. Exceptional research credentials, such as published work, significant open-source contributions, or a strong record of scientific rigor applied in industry. What to Expect as Part of MassMutual and the Team Regular meetings with the AI & Data Science team Focused one-on-one meetings with your manager Networking opportunities including access to Asian, Hispanic/Latinx, African American, women, LGBTQIA+, veteran and disability-focused Business Resource Groups Access to learning content on Degreed and other informational platforms Your ethics and integrity will be valued by a company with a strong and stable ethical business with industry leading pay and benefits MassMutual is an equal employment opportunity employer. We welcome all persons to apply. If you need an accommodation to complete the application process, please contact us and share the specifics of the assistance you need. California residents: For detailed information about your rights under the California Consumer Privacy Act (CCPA), please visit our California Consumer Privacy Act Disclosures page.

The Opportunity MassMutual's AI & Data Science team is seeking an impact-driven Lead AI Engineer to join our high-performing, cross-functional team. In this role, you will lead the design, deployment, and production scaling of advanced AI solutions that solve complex, high-value problems across the enterprise. You'll architect and deliver generative AI, agentic AI, and LLM-based systems by applying rigorous scientific methods, writing high-quality production code, and communicating results to senior leadership. The Team This is a unique opportunity to work alongside experts in applied AI, statistics, and computer science. The team operates at the intersection of cutting-edge research and enterprise delivery, building AI solutions that shape the future of MassMutual and the life insurance industry at large. We partner closely with technology and business stakeholders across the organization, and we invest in growth through a culture of peer learning, candid feedback, and shared technical standards. This team is defined by a shared commitment to scientific and engineering excellence, meaningful work, and the kind of collaboration that makes challenging problems tractable. The Impact Architect, build, and lead end-to-end AI solutions supporting a range of enterprise use cases-from ideation through production deployment and monitoring-using LLMs, agentic AI, machine learning, and probabilistic modeling, with accountability for reliability, performance, and maintainability. Design and conduct rigorous evaluations of AI system performance, including experimentation, benchmarking across foundation models, and quantitative analysis, to validate approaches and inform technical decisions. Drive innovation by identifying emerging technologies, translating cutting-edge research into practical applications, and establishing team-wide best practices in AI development and responsible AI deployment. Build rapid prototypes to test and validate AI approaches and deliver production-grade AI-powered applications (e.g., intelligent interfaces, dashboards, automated workflows) when solutions prove viable. Collaborate with engineering teams to build robust, production-grade AI pipelines and APIs that integrate into the broader enterprise technology ecosystem. Influence senior leadership by aligning AI initiatives with enterprise strategy and communicating complex technical concepts and findings in clear, actionable terms. Mentor and develop junior talent, fostering a culture of technical excellence, scientific rigor, and continuous learning across the team. The Minimum Qualifications 7+ years of experience in data science, machine learning, or AI engineering, with a track record of delivering impactful AI/ML solutions at scale. Deep expertise in machine learning, statistics, NLP, and LLMs, including generative AI, agentic architectures, prompt engineering, and LLM evaluation across a variety of foundation models and benchmarks. Demonstrated ability to build, deploy, and scale production AI systems from architecture planning through orchestration, monitoring, and end-user delivery. Strong programming skills in Python, with the ability to write clean, well-tested, production-quality code, including familiarity with Docker, Kubernetes, and other orchestration and deployment frameworks. M.S. or Ph.D. in Computer Science, Statistics, Applied Mathematics, Electrical Engineering, Physics, or a related quantitative field. The Ideal Qualifications Familiarity with agentic AI tooling ecosystems, such as Bedrock AgentCore, AWS Strands, Azure, and MCP/A2A protocols. Experience developing and evaluating AI systems in a regulated industry, with a strong understanding of compliance and privacy standards. Breadth across AI and data science methods-including classical ML, causal inference, optimization, and Bayesian approaches-with comfort moving across techniques as problems demand. Proficiency in SQL and database design; familiarity with cloud-native data platforms, vector databases, and semantic search. Exceptional ability to translate complex AI concepts and quantitative findings into clear insights for non-technical stakeholders and senior leadership. Exceptional research credentials, such as published work, significant open-source contributions, or a strong record of scientific rigor applied in industry. What to Expect as Part of MassMutual and the Team Regular meetings with the AI & Data Science team Focused one-on-one meetings with your manager Networking opportunities including access to Asian, Hispanic/Latinx, African American, women, LGBTQIA+, veteran and disability-focused Business Resource Groups Access to learning content on Degreed and other informational platforms Your ethics and integrity will be valued by a company with a strong and stable ethical business with industry leading pay and benefits MassMutual is an equal employment opportunity employer. We welcome all persons to apply. If you need an accommodation to complete the application process, please contact us and share the specifics of the assistance you need. California residents: For detailed information about your rights under the California Consumer Privacy Act (CCPA), please visit our California Consumer Privacy Act Disclosures page.

The Opportunity MassMutual's AI & Data Science team is seeking an impact-driven Lead AI Engineer to join our high-performing, cross-functional team. In this role, you will lead the design, deployment, and production scaling of advanced AI solutions that solve complex, high-value problems across the enterprise. You'll architect and deliver generative AI, agentic AI, and LLM-based systems by applying rigorous scientific methods, writing high-quality production code, and communicating results to senior leadership. The Team This is a unique opportunity to work alongside experts in applied AI, statistics, and computer science. The team operates at the intersection of cutting-edge research and enterprise delivery, building AI solutions that shape the future of MassMutual and the life insurance industry at large. We partner closely with technology and business stakeholders across the organization, and we invest in growth through a culture of peer learning, candid feedback, and shared technical standards. This team is defined by a shared commitment to scientific and engineering excellence, meaningful work, and the kind of collaboration that makes challenging problems tractable. The Impact Architect, build, and lead end-to-end AI solutions supporting a range of enterprise use cases-from ideation through production deployment and monitoring-using LLMs, agentic AI, machine learning, and probabilistic modeling, with accountability for reliability, performance, and maintainability. Design and conduct rigorous evaluations of AI system performance, including experimentation, benchmarking across foundation models, and quantitative analysis, to validate approaches and inform technical decisions. Drive innovation by identifying emerging technologies, translating cutting-edge research into practical applications, and establishing team-wide best practices in AI development and responsible AI deployment. Build rapid prototypes to test and validate AI approaches and deliver production-grade AI-powered applications (e.g., intelligent interfaces, dashboards, automated workflows) when solutions prove viable. Collaborate with engineering teams to build robust, production-grade AI pipelines and APIs that integrate into the broader enterprise technology ecosystem. Influence senior leadership by aligning AI initiatives with enterprise strategy and communicating complex technical concepts and findings in clear, actionable terms. Mentor and develop junior talent, fostering a culture of technical excellence, scientific rigor, and continuous learning across the team. The Minimum Qualifications 7+ years of experience in data science, machine learning, or AI engineering, with a track record of delivering impactful AI/ML solutions at scale. Deep expertise in machine learning, statistics, NLP, and LLMs, including generative AI, agentic architectures, prompt engineering, and LLM evaluation across a variety of foundation models and benchmarks. Demonstrated ability to build, deploy, and scale production AI systems from architecture planning through orchestration, monitoring, and end-user delivery. Strong programming skills in Python, with the ability to write clean, well-tested, production-quality code, including familiarity with Docker, Kubernetes, and other orchestration and deployment frameworks. M.S. or Ph.D. in Computer Science, Statistics, Applied Mathematics, Electrical Engineering, Physics, or a related quantitative field. The Ideal Qualifications Familiarity with agentic AI tooling ecosystems, such as Bedrock AgentCore, AWS Strands, Azure, and MCP/A2A protocols. Experience developing and evaluating AI systems in a regulated industry, with a strong understanding of compliance and privacy standards. Breadth across AI and data science methods-including classical ML, causal inference, optimization, and Bayesian approaches-with comfort moving across techniques as problems demand. Proficiency in SQL and database design; familiarity with cloud-native data platforms, vector databases, and semantic search. Exceptional ability to translate complex AI concepts and quantitative findings into clear insights for non-technical stakeholders and senior leadership. Exceptional research credentials, such as published work, significant open-source contributions, or a strong record of scientific rigor applied in industry. What to Expect as Part of MassMutual and the Team Regular meetings with the AI & Data Science team Focused one-on-one meetings with your manager Networking opportunities including access to Asian, Hispanic/Latinx, African American, women, LGBTQIA+, veteran and disability-focused Business Resource Groups Access to learning content on Degreed and other informational platforms Your ethics and integrity will be valued by a company with a strong and stable ethical business with industry leading pay and benefits MassMutual is an equal employment opportunity employer. We welcome all persons to apply. If you need an accommodation to complete the application process, please contact us and share the specifics of the assistance you need. California residents: For detailed information about your rights under the California Consumer Privacy Act (CCPA), please visit our California Consumer Privacy Act Disclosures page.

Systems Engineer II - Security THIS ROLE WILL BE BASED ON-SITE, IN OUR IRVING, TX. OFFICE We are Lennar Lennar is one of the nation's leading homebuilders, dedicated to making an impact and creating an extraordinary experience for their Homeowners, Communities, and Associates by building quality homes and providing exceptional customer service, giving back to the communities in which we work and live in, and fostering a culture of opportunity and growth for our Associates throughout their career. Lennar has been recognized as a Fortune 500 company and consistently ranked among the top homebuilders in the United States. Join a Company that Empowers you to Build your Future The Systems Engineer II - Security is a mid-level position responsible for enhancing and maintaining the security of the organization's information technology infrastructure. The Systems Engineer II - Security role is responsible for designing, implementing, and operating enterprise identity and access controls across IAM, IGA, and PAM platforms to ensure the right users and workloads have the right access at the right time. This role reduces identity-related risk by enforcing least privilege, strengthening authentication, and governing privileged access in alignment with security and regulatory requirements. A career with purpose. A career built on making dreams come true. A career built on building zero defect homes, cost management, and adherence to schedules. Your Responsibilities on the Team Systems Security: Support enterprise IAM solutions that collectively deliver single sign-on (SSO), multifactor authentication (MFA), identity governance and administration, and privileged access management for all types of identities, including on-premises, hybrid, cloud-only, non-human (service accounts), and application-based credentials (API keys, tokens). Engineer and operate IGA capabilities, including joiner mover leaver workflows, access request and approval, automated provisioning/de provisioning, and role based access control (RBAC/ABAC) Implement and manage PAM platforms for privileged account onboarding, credential vaulting, password rotation, session monitoring/recording, and just in time (JIT) elevation. Design and implement identity and access controls for AI agents and non-human identities (service accounts, bots, APIs, workloads), including lifecycle management, secrets management, least-privilege roles, and monitoring of machine-to-machine access in alignment with Zero Trust principles. Monitor identity and privileged access activities, analyze logs and alerts, and support incident response and forensic investigations related to compromised identities or misuse of privilege. Support audit, compliance, and certification efforts by providing evidence, improving control design, and remediating findings related to IAM, IGA, and PAM. Troubleshoot complex IAM/IGA/PAM issues, perform root cause analysis, and drive continuous improvement and modernization of identity platforms. Collaborate with security architecture, infrastructure, application, and DevOps teams to embed identity security and Zero Trust principles in new solutions and strategic programs. Document architectures, standards, runbooks, and knowledge articles, and provide guidance and training to operations and application teams on identity security best practices Participate in Proof of Concepts and product evaluations of new and emerging Identity security services and technologies. May provide mentorship and support to various junior security engineers and security operations team members. Requirements Education: Bachelor's degree required in Computer Science, Cybersecurity, Engineering, or related field. Experience: 4-5 years of hands-on cybersecurity engineering experience with exposure to IAM. 4+ years of relevant work experience in security engineering, with a focus on concepts and technologies in Identity & Access Management (IAM) like SailPoint, Delinea, CyberArk, Entra ID, Ping Identities 2+ years of relevant work experience with Identity and Access Management solutions, including the implementation and configuration of solutions for Single Sign-On (SSO), Multifactor Authentication (MFA), and various identity integration protocols (SAML, OIDC). Experience building and maintaining SailPoint connectors, aggregation and provisioning jobs, roles/entitlements, and workflows for HR-driven JML processes. Experience administering Microsoft Entra ID, including users, groups, roles, app registrations, and enterprise applications. Working knowledge of solutions for Identity Governance and Administration, Privileged Access Management, and access control models such as RBAC, ABAC, PBAC, and FGAC Certifications: Any Certified Information Systems Security Professional (CISSP), CompTIA Security+, Certified Identity and Access Manager (CIAM), or similar advanced cloud security certifications preferred. Additional Skills, Knowledge, and Experience: Working knowledge of cloud-based Identity Providers, access controls, and hybrid federated IAM architectures. Experience in designing, configuring, and administering SailPoint Identity Security Cloud for identity lifecycle, access request, certifications, and policy/SoD controls. Strong knowledge and experience with Microsoft Active Directory (AD) Domain Services, management of AD users and security groups, and security best practices for configuring AD infrastructure, policies, group policy objects. Experience with implementing access control mechanisms, such as authentication policies, identity lifecycle management (provisioning, deprovisioning), and methods for authorization management. Strong skills in developing visual design documentation (Visio, Lucid), oral presentation skills, problem solving / critical thinking, and decision-making skills. Strong verbal and written communication skills. Ability to facilitate productive meetings and work comfortably in a team-oriented environment. Personal Attributes: Team Player: Ability to work collaboratively with senior engineers, IT teams, and other stakeholders to achieve shared goals. Communication: Effective written and verbal communication skills, with the ability to explain technical concepts to non-technical audiences. Ability to leverage communication skills to ensure a strong commitment to customer service. Detail-Oriented: Attention to detail and consideration of the non-technical components necessary for successfully executing projects and initiatives. Adaptability: Ability to balance multiple competing prioities in a fast-paced environment. Minimal Supervision: Comfortable with executing workstreams independently with a positive and self-motivated drive. Exercise sound judgement in complex situations. Additional Requirements: Continuous Learning: Commitment to staying current with industry trends and pursuing relevant certifications and training. Travel: Willingness to travel occasionally This role is ideal for a motivated systems security engineer looking to use and build upon their existing technical skillsets. This role will deliver significant and essential security services necessary to protect the business operations of a large-scale enterprise. If you are passionate about cybersecurity and eager to grow in a fast-paced, collaborative environment, we encourage you to apply. Life at Lennar At Lennar, we are committed to fostering a supportive and enriching environment for our Associates, offering a comprehensive array of benefits designed to enhance their well-being and professional growth. Our Associates have access to robust health insurance plans, including Medical, Dental, and Vision coverage, ensuring their health needs are well taken care of. Our 401(k) Retirement Plan, complete with a $1 for $1 Company Match up to 5%, helps secure their financial future, while Paid Parental Leave and an Associate Assistance Plan provide essential support during life's critical moments. To further support our Associates, we provide an Education Assistance Program and up to $30,000 in Adoption Assistance, underscoring our commitment to their diverse needs and aspirations. From the moment of hire, they can enjoy up to three weeks of vacation annually, alongside generous Holiday, Sick Leave, and Personal Day policies. Additionally, we offer a New Hire Referral Bonus Program, significant Home Purchase Discounts, and unique opportunities such as the Everyone's Included Day. At Lennar, we believe in investing in our Associates, empowering them to thrive both personally and professionally. Lennar Associates will have access to these benefits as outlined by Lennar's policies and applicable plan terms. Visit to view our suite of benefits. Join the fun and follow us on social media to see what's happening at our company, and don't forget to connect with us on Lennar: Overview LinkedIn for the latest job opportunities. Lennar is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws.

Stefanini Group is hiring! Stefanini is looking for a Java Developer, Dearborn, MI For quick apply, please reach out to Adil Khan at 248-728- 6424/ We are looking for a Java Developer who will be responsible for designing, developing, testing, and maintaining software applications and products to meet customer needs. They are involved in the entire software development lifecycle, including designing software architecture, writing code, testing for quality, and deploying software to meet customer requirements. Full-stack software engineering roles, involving the development of all software components-including user interfaces and server-side applications-also fall within this job function. Key Responsibilities Lead and manage cloud migration projects from initiation through completion, ensuring timely delivery and adherence to scope and budget constraints. Develop and manage detailed migration plans, including timelines, resource allocation, and risk management strategies. Oversee the assessment, planning, and execution of application migrations across infrastructure, data, and application layers. Provide technical guidance on cloud architecture, security, and performance best practices. Collaborate closely with architects, engineers, product owners, and business stakeholders to support execution of the PLM cloud migration strategy. Troubleshoot and resolve migration-related issues by working with technical teams to identify and implement solutions. Serve as the primary contact for PDOs and Skill Team SPCOs, providing regular updates on migration progress, risks, and issues. Collaborate with business units to understand their requirements and ensure alignment with business goals. Provide deep technical expertise in integrating PLM systems with other enterprise applications, including ERP, CRM, and manufacturing systems. Identify potential risks and develop strategies to mitigate challenges during the migration process. Ensure migrations comply with organizational policies, industry standards, and regulatory requirements. Conduct post-migration reviews to assess project success, document lessons learned, and recommend improvements for future projects. Evaluate and enhance migration processes, tools, and methodologies to improve efficiency and effectiveness. Stay current with GCP updates, industry trends, and emerging technologies to incorporate best practices into migration strategies. Share knowledge and mentor team members to build internal expertise and capabilities. Skills Required Software Development, Spring Boot, REST APIs, Java, Machine Learning, AWS, GCP, COBOL Skills Preferred Product Management, J2EE, Artificial Intelligence & Expert Systems, Jenkins Experience Required 15+ years of hands-on Java development experience, including Java 8/11/17+, Core Java, Spring Boot, Spring Framework, and RESTful API design and development. Strong understanding of object-oriented design, microservices architecture, and enterprise integration patterns. Experience with build and CI/CD tools, including Maven or Gradle, Jenkins, and Git. Experience with unit testing frameworks such as JUnit and Mockito. Ability to design, develop, and maintain Java-based services that interface with legacy systems through APIs, message queues, batch integration, or similar mechanisms. Demonstrated experience modernizing legacy applications-including mainframe, monolithic, or on-premises systems-into cloud-native architectures using Java. Hands-on experience re-platforming or re-architecting legacy Java- or COBOL-based systems into containerized microservices using technologies such as Docker and Kubernetes. Experience with cloud platforms such as AWS, Azure, or GCP, as well as cloud-native patterns including 12-factor applications, event-driven architecture, and serverless technologies where applicable. Familiarity with the strangler-fig pattern, API-led integration, and other legacy-to-cloud migration strategies. Ability to assess legacy application portfolios and recommend modernization roadmaps, including rehost, replatform, refactor, and rearchitect approaches. Experience Preferred Practical experience building or integrating Generative AI solutions, including LLM-based applications, RAG pipelines, prompt engineering, embeddings, and vector databases. Familiarity with Generative AI frameworks and tools such as LangChain, OpenAI or Azure OpenAI APIs, Hugging Face, or similar technologies. Experience deploying Generative AI capabilities into enterprise applications, including chatbots, document summarization, code assistance, and data extraction solutions. Understanding of responsible AI practices, including data privacy, model governance, and output validation in enterprise contexts. Experience leveraging Generative AI to accelerate cloud-native modernization efforts, such as AI-assisted code conversion and refactoring, legacy code comprehension, automated test generation, and documentation of undocumented legacy logic. Familiarity with using Generative AI tools to analyze legacy codebases and assist in re-architecting them into cloud-native Java solutions. Education Required Bachelor's degree Education Preferred Certification program Listed salary ranges may vary based on experience, qualifications, and local market. Also, some positions may include bonuses or other incentives Stefanini takes pride in hiring top talent and developing relationships with our future employees. Our talent acquisition teams will never make an offer of employment without having a phone conversation with you. Those face-to-face conversations will involve a description of the job for which you have applied. We will also speak with you about the process, including interviews and job offers. About Stefanini Group The Stefanini Group is a global provider of offshore, onshore and near shore outsourcing, IT digital consulting, systems integration, application, and strategic staffing services to Fortune 1000 enterprises around the world. Our presence is in countries like the Americas, Europe, Africa, and Asia, and more than four hundred clients across a broad spectrum of markets, including financial services, manufacturing, telecommunications, chemical services, technology, public sector, and utilities. Stefanini is a CMM level 5, IT consulting company with a global presence. We are a CMM Level 5 company.

Genesis10 is currently seeking an Enterprise Architect for a direct hire opportunity with a Major Financial Services Firm located in Camas, WA or Plano, TX. The Enterprise Architect will bring strong cross-domain expertise, strategic thinking, and executive presence. This is a strategic leadership role where you will work across domains to lead enterprise-wide architecture decisions for scalable data and AI modernization. Reporting to the Vice President, Enterprise Architecture and Standards, you will be a facilitator and diplomat who can influence CXO-level stakeholders while remaining deeply involved in execution. In addition to the base salary, this position is eligible for a discretionary bonus based on firm and individual performance. Responsibilities: Drive enterprise level architecture across multiple business domains, ensuring alignment with organizational strategy Lead discussions with senior stakeholders and bring clarity to complex technical decisions Lead the standardization of metadata practices across domains, ensuring discoverability, lineage, and governance Design and evolve enterprise-level semantic data models, including logical and conceptual models, ontologies, and domain definitions Partner with product, engineering, data, and AI teams to ensure data supports reporting, analytics, and AI use cases Provide feedback that directly shapes the next generation of AI models Knowledge of Machine Learning Operations (MLOps) workflows and tools for deploying, managing, and monitoring AI models in production Actively participate in design, discussions, and delivery-not just governance-with hands on engagement Review AI-generated code to ensure it is accurate, efficient, and high quality Stay current on AI and data trends to help the organization evolve Requirements: 15 years of experience in IT 5 years of experience in: An Enterprise Architect role AI and ML Architectures 2 years of experience in: Data-focused A1 tools Leading Enterprise Architecture initiatives Proficient in tools such as Purview, Unity catalog, Erwin, or other semantic/metadata platforms Deep experience with Microsoft Azure and their AI and data services Experience working with the Financial Services Industry Bachelor's degree in computer science, Information Systems, Engineering, or equivalent work experience Pay range: $200,000 - $240,000 per year If you have the described qualifications and are interested in this exciting opportunity, please apply! Ranked a Top Staffing Firm in the U.S. by Staffing Industry Analysts for six consecutive years, Genesis10 puts thousands of consultants and employees to work across the United States every year in contract, contract-for-hire, and permanent placement roles. With more than 300 active clients, Genesis10 provides access to many of the Fortune 100 firms and a variety of mid-market organizations across the full spectrum of industry verticals. For contract roles, Genesis10 offers the benefits listed below. If this is a perm-placement opportunity, our recruiter can talk you through the unique benefits offered for that particular client. Benefits of Working with Genesis10: Access to hundreds of clients, most who have been working with Genesis10 for 5-20 years. The opportunity to have a career-home in Genesis10; many of our consultants have been working exclusively with Genesis10 for years. Access to an experienced, caring recruiting team (more than 7 years of experience, on average.) Behavioral Health Platform Medical, Dental, Vision Health Savings Account Voluntary Hospital Indemnity (Critical Illness & Accident) Voluntary Term Life Insurance 401K Sick Pay (for applicable states/municipalities) Commuter Benefits (Dallas, NYC, SF, and Illinois) For multiple years running, Genesis10 has been recognized as a Top Staffing Firm in the U.S., as a Best Company for Work-Life Balance, as a Best Company for Career Growth, for Diversity, and for Leadership, amongst others. To learn more and to view all our available career opportunities, please visit us at our website. Genesis10 is an Equal Opportunity Employer. Candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

Position Title: Staff Data Scientist Description: Staff Data Scientist Location: Beachwood, OH Shift: Monday - Friday 8am - 5pm (Onsite 4 days a week) (Possible remote for the right candidate) Position Summary: The Staff Data Scientist will be a key role in the Data Science and Analytics team tasked with providing technical leadership for the establishment of enterprise wide capabilities in data science, AI and predictive analytics. The Staff Data Scientist will typically work on 3-5 large projects concurrently that have organization-wide impact. In addition to these projects, the Staff Data Scientist will provide technical consultation, advice and training on all major on-going Data Science and Analytics projects. When required, the Staff Data Scientist will also act as a project manager where vendors, suppliers and consultants are engaged on key strategic and emerging technology initiatives. Major Responsibilities: Identifying High Value Analytics & AI Opportunities Partner with business leaders to identify opportunities where predictive analytics, machine learning, or generative AI can improve productivity, reduce cost, or unlock new capabilities. Develop clear business cases and ROI models to prioritize initiatives and communicate value to senior leadership. Lead Data Science Projects Translate complex business requirements into robust, scalable technical solutions. Select and implement appropriate modeling techniques, including classical ML, deep learning, generative AI, and reinforcement learning where applicable. Oversee the full model lifecycle: data exploration, feature engineering, model development, evaluation, deployment, monitoring, and continuous improvement. Ensure solutions are production ready, maintainable, and aligned with MLOps best practices. Drive organization wide adoption of models and AI systems through clear communication, documentation, and stakeholder engagement. Technical Guidance & Thought Leadership Provide expert consultation on ML algorithms, model tuning, experimentation frameworks, and cloud native data engineering patterns. Mentor data scientists, ML engineers and AI engineers; support skill development in areas such as forecasting, ML modeling, generative AI, vector databases, and modern ETL/ELT workflows. Contribute to the development of internal standards, reusable components, and best practice guidelines. Project Management Develop and maintain project plans, milestones, and communication strategies for strategic initiatives. Facilitate regular updates with stakeholders, executives, and cross functional partners. Coordinate with vendors, consultants, and technology partners when external expertise is required Lead technology change in Data Science, Analytics and AI Evaluate emerging technologies including generative AI platforms, MLOps tools, cloud services, and data engineering frameworks to determine applicability and business value. Recommend and influence adoption of modern, flexible, and scalable technologies that support a unified enterprise data and AI platform. Drive experimentation and prototyping to accelerate innovation and reduce time to value. Qualifications: Master's Degree required; preferred concentrations in Engineering, Operations Research, Statistics, Applied Math, Computer Science, Data Science or related quantitative field. PhD preferred in Engineering, Operations Research, Statistics, Applied Math, Computer Science, Data Science or related quantitative field. 7+ years of experience along with a PhD in a related field OR 10+ years of experience along with a Master's degree in a related field required. Advanced experience developing and deploying machine learning models using Python and modern ML frameworks (e.g., Scikitlearn, PyTorch, TensorFlow). Strong applied expertise across core ML techniques, including regression, tree based models, clustering, deep learning, and NLP. Familiarity with generative AI and LLMs, including prompt engineering, finetuning, embeddings, and vector databases. Solid understanding of MLOps practices, including CI/CD for ML, automated training pipelines, model versioning, monitoring, and model governance. Hands on experience with cloud based ML platforms (AWS, Azure, or GCP) and containerization/orchestration tools such as Docker and Kubernetes. Working knowledge of modern data ecosystems (Snowflake, Redshift) and the ability to collaborate effectively with data engineering teams when needed. Advanced skill in statistical modeling, SQL, and database concepts required. Demonstrated experience leading small technical teams or pods, providing mentorship and technical direction. Familiarity with Logistics industry is preferred. Regular, predictable, full attendance is an essential function of the job Willingness to travel as necessary, work the required schedule, work at the specific location required, complete Penske employment application, submit to a background investigation (to include past employment, education, and criminal history) and drug screening are required. Physical Requirements: -The physical and mental demands described here are representative of those that must be met by an associate to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. -The associate will be required to: read; communicate verbally and/or in written form; remember and analyze certain information; and remember and understand certain instructions or guidelines. -While performing the duties of this job, the associate may be required to stand, walk, and sit. The associate is frequently required to use hands to touch, handle, and feel, and to reach with hands and arms. The associate must be able to occasionally lift and/or move up to 25lbs/12kg. -Specific vision abilities required by this job include close vision, distance vision, peripheral vision, depth perception and the ability to adjust focus. Penske is an Equal Opportunity Employer. About Penske Logistics Penske Logistics engineers state-of-the-art transportation, warehousing and freight management solutions that deliver powerful business results for market-leading companies. With operations in North America, South America, Europe and Asia, Penske and its associates help businesses move forward by increasing visibility and driving down supply-chain costs. Visit Penske Logistics to learn more. Job Category: Information Technology Job Family: Analytics & Intelligence Address: 3000 Auburn Dr Primary Location: US-OH-Beachwood Employer: Penske Logistics LLC Req ID: Requirements PI

Job Overview: Pay Range $45.96hr - $50.96hr Requirement/Must Have: 1+ years of experience in data analysis, statistical modeling, and ML development using Python (pandas, numpy, scikit-learn, scipy, curve fitting, object-oriented programming). Ability to build multi-scenario models to test assumptions and evaluate alternative planning outcomes. Foundational to intermediate experience with ML frameworks and methodologies (scikit-learn, XGBoost, or similar). Understanding of model validation metrics (R , MAE, RMSE, cross-validation, custom scoring functions). Proficiency in SQL for querying, joining tables, data manipulation, and interpreting complex queries. Understanding of statistical modeling, hypothesis testing, and experimental design. Ability to independently explore enterprise datasets and identify patterns, gaps, and opportunities. Experience handling messy data, identifying inconsistencies, and standardizing formats across heterogeneous systems. Experience merging multiple datasets from various enterprise data sources (SAP, Salesforce, Databricks, ERP/CRM). Sharp eye for finding outliers, errors, and unusual patterns in structured and unstructured data. Understanding of data modeling concepts across heterogeneous systems. Experience developing models for scenario modeling and predictive use cases. Familiarity with Large Language Models (LLMs) and basic prompt engineering techniques for practical business applications. Ability to review existing dashboards, ML models, and reports to understand design patterns, business requirements, and underlying data sources. Strong capability to read and interpret complex SQL queries to understand data flows and business logic. Skills to trace data lineage, review prepared data sources, and comprehend underlying data structures. Experience working with Data Engineers to ensure data requirements are correctly implemented at pipeline and infrastructure level. Responsibilities: Analyze quality data from multiple enterprise systems (SAP, Salesforce, Databricks, Power BI, labor systems, finance data) to identify patterns, gaps, and opportunities for data-driven improvements. Work with Program Managers and/or Operations leaders to define which data assets are relevant for business use cases and specify how data from different systems should be accessed, interpreted, and used. Transform structured/unstructured datasets (often 100k+ rows) into actionable insights. Conduct data quality checks and identify/resolve data defects and abnormalities across enterprise platforms. Develop and validate Machine Learning models that support demand forecasting, scenario modeling, and predictive use cases for short-term and long-term business goals. Document analytical findings, model performance, and data definitions clearly to ensure transparency and reproducibility across the team. Experience working with Data Engineers to ensure data requirements are correctly implemented; ability to build and maintain Python-based data pipelines for ETL, model training, and automated forecasting workflows. Translate business technical data challenges into concrete data science and AI/ML problem statements, acting as the domain-aware bridge between Engineering/Operations and the Digital team. Leverage Large Language Models (LLMs) and prompt engineering to build intelligent tools that augment human decision-making and automate workflows. Design and execute scenario planning models to test business assumptions (demand forecasts, resource capacity, cost projections) and evaluate 'what-if' outcomes for strategic decision-making. Track project execution data across P6 (Primavera) and other project management systems, linking planning assumptions to actual execution performance. Support variance analysis between planned assumptions (forecast hours, budgets, timelines) and actual project execution data to identify gaps, root causes, and trends. Build automated tracking solutions that monitor assumption validity as projects progress through lifecycle stages (planning design execution closeout). Collaborate with Program Managers to refine planning assumptions based on execution learnings and historical pattern analysis. Provide data pipeline and data to build executive dashboards that visualize assumption-to-execution alignment, highlighting projects at risk due to assumption breakdown. Review and analyze existing dashboards, models, and data pipelines to understand design patterns, business requirements, and data flows. Read and interpret SQL queries, business logic, and semantic models embedded in current reports and analytical systems. Understand underlying data structures and prepared data sources to support maintenance and enhancement. Identify opportunities to optimize or consolidate existing reporting and modeling assets. Maintain consistency with established data standards and best practices. Translate complex data findings and model outputs into clear, actionable business insights for both technical and non-technical audiences. Resolve customer and internal user queries related to model outputs, data insights, or data defects. Support the Operations team in delivering centralized data analysis-based reporting solutions (including KPI), providing harmonized insights and KPIs to business stakeholders across global business lines. Collaborate closely with cross-functional Data analysts and Data engineers to ensure data requirements are correctly understood and implemented at pipeline and infrastructure level. Build and maintain a deep understanding of Semantic Data Models to ensure consistent data interpretation across applications and business systems. Stay current with the latest advancements in AI, ML, and data science, proactively proposing new approaches that could enhance our solutions. Contribute to the evolution of Engineering Data Quality, bringing innovative ideas and a forward-thinking mindset to continuously improve our modeling and tooling landscape. Nice to Have: Experience with TensorFlow, PyTorch, neural networks, or deep learning applications. Experience with pytest or similar frameworks for data science code quality. Experience with P6 (Primavera), MS Project, or similar project execution systems. Model versioning, experiment tracking (MLflow, Weights & Biases), deployment basics. Familiarity with Azure, AWS, or GCP for data science workflows. Experience with fine-tuning, RAG (Retrieval-Augmented Generation), or agent frameworks. Understanding of data governance principles and responsible AI practices. First-hand experience with SAP, Salesforce, Databricks, or similar ERP/CRM systems from a data consumption perspective. Skills: Strong verbal and written communication skills. Excellent communication and presentation skills. Ability to communicate effectively with stakeholders. Analytical thinking with strong problem-solving abilities. Technical curiosity and willingness to learn new tools and techniques. Collaborative mindset and ability to work in dynamic environments. Self-motivated with a strong sense of accountability. Proactive communication style. Benefits Our Benefits Include: Medical, Dental, and Vision Insurance 401(k) Retirement Plan Health Savings Account (HSA) Disability Insurance (Short-Term and Long-Term) Life and AD&D Insurance Paid Sick Leave (where required by applicable state or local law) Supplemental Insurance Plans Identity Theft Protection Pet Insurance Employee Wellness Programs Employee Assistance Program (EAP) Career Growth and Professional Development Opportunities Disclaimer: Benefits eligibility, accrual rates, and usage limits may vary based on employment status, length of service, and work location. Paid Sick Leave is provided in strict accordance with applicable state and municipal mandates. Cynet Systems Inc. reserves the right to modify, amend, or terminate any benefit plans at any time in accordance with applicable laws. About Cynet Systems Founded in 2010 and headquartered in the Washington, DC metro area, Cynet Systems Inc. is a leading technology staffing and workforce solutions company serving Fortune 500 companies, government agencies, and enterprise organizations across the United States and Canada. We deliver agile, scalable talent solutions across IT, engineering, life sciences, clinical, and professional staffing, powered by a high-performing recruitment engine operating across North America and Asia. As a nationally and locally certified Minority Business Enterprise (MBE), Cynet Systems is committed to helping organizations build high-performing teams while empowering professionals to grow rewarding careers. Our organization is certified to ISO 9001, ISO 14001, ISO 27001, and SOC 2 Type II standards, reflecting our commitment to quality, security, operational excellence, and customer success.

About Bering Straits Professional Services Paragon offers a wide range of environmental investigation, consulting, compliance, and remediation services as well as IT solutions, Facility O&M, Materiel Support, Supply and Security to both private- and public-sector clients throughout Alaska and the Continental U.S. Paragon's experienced professional staff is dedicated to producing high-quality documentation and providing safe field execution to support its clients' projects in line with local, state and federal guidelines and regulations. About this position: Sr. Cybersecurity Incident Response Specialist Location - Washington, DC The Essential Duties and Responsibilities are intended to present a descriptive list of the range of duties performed for this position and are not intended to reflect all duties performed within the job. Other duties may be assigned. To perform this job successfully, an individual must be able to satisfactorily perform each essential duty. 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 of the position. Wage/Salary Range: $100k - $120k Applicants will be notified via phone or email within ten (10) business days of submittal. Essential Duties & Responsibilities Member of the SOC team which provides 24 hours per day, 7 days per week, 365 days per year monitoring and incident response services for the organization's Network, Systems, Applications, and Web services. Provide senior level cybersecurity incident response expertise in support of the client's Incident Response processes and procedures. Develop operational baselines such data flows and application interactions to enhance SOC's ability to respond to incidents. Prepare and manage playbooks and relevant scenarios in addition to narratives and visual diagrams and review continuously, in compliance with NIST SP 800-61 and Government guidance. Follow current guidance from NIST 800-61, Federal Incident Notification Guidelines, CISA's Incident Response and Vulnerability Playbook, and client guidance. Monitor system status and sensor data from deployed sensors and triage for validity from Security Information and Event Management (SIEM) System, email, texts, phone calls and all enterprise managed dashboards. Analyze all sources including network traffic, identity, fault, performance, and bandwidth information, alerts and data to augment detection of network anomalies and unauthorized activity. Meet regularly with client stakeholders to develop content, analytic rules, alerts, dashboards, automation and identify ways to improve availability and efficiency of client's incident response program. Categorize, Prioritize, and Report on cybersecurity events in accordance with (IAW) SOPs and other relevant policies documents. Implement cybersecurity mitigations leveraging client tools and systems. Create and escalate cybersecurity-related investigations to both internal and external entities such as DHS or other Government Agencies with client and Federal defined timelines. Manage, coordinate, and respond to FOIA, audits, data calls, e-discovery and information requests. Schedule and execute incident response tabletop exercises with each client FISMA system on an annual basis. Review and handle phishing messages reported by client staff. Required (Minimum Necessary) Qualifications Education Requirements: High School or GED-General Educational Development-GED Diploma Bachelor's degree in computer science or equivalent is preferred Level of Experience Requirements: Minimum of five years hands-on experience Proven experience detecting, triaging, and responding to cyber incidents across enterprise networks and cloud environments. Knowledge, Skills, Abilities, and Other Characteristics Proficiency with SIEM, EDR/XDR platforms, and forensic tools. Strong understanding of threat actor TTPs, MITRE ATT&CK framework, and incident containment strategies. Ability to analyze network traffic, logs, and endpoint telemetry to identify malicious activity. Familiarity with malware analysis, reverse engineering basics, and memory analysis concepts Experience developing and tuning detection rules, playbooks, and automated response workflows. Working knowledge of incident response frameworks (e.g., NIST SP 800-61, SANS). Understanding of vulnerability management, threat intelligence integration, and SOC metrics/reporting. Understanding of basic computer and networking technologies. Windows and Linux/Unix operating systems Networking technologies (routing, switching, VLANs, subnets, firewalls) Common networking protocols - SSH, SMB, SMTP, FTP/SFTP, HTTP/HTTPS, DNS, etc. Common enterprise technologies - Active Directory, Group Policy, and the Microsoft Azure suite of cloud services. Understanding of current system logging technology and retrieving information from a plethora of technology platforms. Ability to work well in a team environment. Self-starter with ability to work with little supervision. Willingness to take on and adapt to new, open-ended tasks for which there is no current standard operating procedure. Ability to research independently and self-teach. Strong analytical and decision-making skills under pressure. Excellent written and verbal communication, including incident documentation and executive briefings. Ability to lead investigations, mentor junior analysts, and collaborate with cross-functional teams. Applicants selected will be subject to a government security investigation and must meet eligibility requirements for access to classified information. Accordingly, U.S. Citizenship is required. Preferred Interest in security/hacking culture. Ability to "think like an attacker" General cybersecurity certifications (one or more of the following preferred): CompTIA Security+ CompTIA Cybersecurity Analyst (CySA+) Certified Ethical Hacker (CEH) GIAC Certified Incident Handler (GCIH) Any cloud security certification, especially: CompTIA Cloud+ Certified Cloud Security Professional (CCSP) Cloud Security Alliance Certificate of Cloud Security Knowledge (CCSK) Any Microsoft 365/Azure cybersecurity certification, especially: Microsoft Certified: Security Operations Analyst Associate (SC-200) Microsoft Certified: Security, Compliance, and Identity Fundamentals (SC-900) Microsoft Certified: Azure Fundamentals (AZ-900) Microsoft Certified: Azure Security Engineer Associate (AZ-500) Familiarity with the Microsoft 365 and Microsoft Azure suite of products, including Microsoft Sentinel and Microsoft 365 Defender. Knowledge of common enterprise technologies, policies, and concepts such as: Microsoft Sentinel SIEM Kusto Query Language (KQL) Mobile device technologies (iOS, Android) Scripting experience (PowerShell, Python, etc.) Microsoft Power BI Azure DevOps Artificial Intelligence (AI) / Machine Learning (ML) expertise In-depth knowledge of AI and ML concepts. How to practically apply AI/ML technologies to enhance cyber threat hunting and incident response capabilities. Experience with specific AI services offered within Microsoft Azure. Supervisory Responsibilities This position will not have supervisory responsibilities. DOT Covered/Safety-Sensitive Role Requirements This position is not subject to federal requirements regarding Department of Transportation "safety-sensitive" functions. Necessary Physical Requirements The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this role. Employees must always maintain a constant state of mental alertness. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. Essential and marginal functions may require maintaining physical condition necessary for bending, stooping, sitting, walking or standing for prolonged periods of time; most of time is spent sitting in a comfortable position with frequent opportunity to move about. Work Environment The work environmental characteristics described here are representative of those that must be borne by an employee to successfully perform the essential functions of the role. Employees must always maintain a constant state of situational awareness. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. Physical Setting: Washington DC Schedule and Flexibility: Full Time in Office Additional Qualifying Factors As a condition of employment, you will be required to pass a pre-employment drug screening and have acceptable background check results. If applicable to the contract, you must also obtain and maintain the appropriate clearance levels required and must also be able to obtain access to military installations. Shareholder Preference BSNC gives hiring, promotion, training, and retention preference to BSNC shareholders, shareholder descendants and shareholder spouses who meet the minimum qualifications for the job. Bering Straits Native Corporation is an equal opportunity employer. All applicants will receive consideration for employment without regard to any status protected by state or federal law, or any other basis prohibited by law.

Stefanini Group is hiring! Stefanini is looking for a GCP Data Engineer, Dearborn, MI For quick apply, please reach out to Parul Singh at / We are looking for Data Engineer who will be responsible for designing, developing, testing, and maintaining software applications and products to meet customer needs. They are involved in the entire software development lifecycle, including designing software architecture, writing code, testing for quality, and deploying software to meet customer requirements. Full-stack software engineering roles, in which employees develop all components of software-including the user interface and server side-also fall within this job function. Key Responsibilities Oversee and contribute to the design, development, and implementation of complex, scalable, and resilient data architectures, including data warehouses, data lakes, and streaming platforms. Lead the creation, maintenance, and optimization of advanced ETL/ELT processes and data pipelines to ingest, transform, and deliver large volumes of data from diverse sources. Ensure data integrity, quality, and performance across all data flows. Assess the requirements of the software application or service and determine the most suitable technology stack, integration method, deployment strategy, and related components. Create high-level software architecture designs that outline the overall structure, components, and interfaces of the application. Define and implement software test strategies, guidelines, policies, and processes in line with organizational vision, industry regulations, and market best practices. Continuously improve performance, optimize applications, and implement new technologies to maximize development efficiency. Develop and maintain back-end applications such as APIs and microservices using server-side languages. Required Skills NoSQL, Kubernetes, Kafka, GCP, Cloud Architecture, Data Architecture, Big Data, Cloud Infrastructure, Apache Spark, BigQuery, Apache Hadoop, Java, Docker, Python, Data Management Preferred Skills GitHub, Machine Learning Required Experience 5+ years of progressive experience in data engineering or a related role, with a significant focus on large-scale data systems. Expert proficiency in programming languages such as Python or Scala. Advanced SQL skills for complex querying, data manipulation, and database design. Extensive experience with big data technologies, such as Apache Spark, Hadoop, Kafka, and Flink. Proven experience with cloud platforms, including AWS, Azure, or GCP, and their data services, such as: AWS Glue, S3, Redshift, and Athena, Azure Data Factory and Databricks, Google BigQuery and Dataflow Strong understanding of data warehousing concepts, data modeling-including dimensional and relational models-and ETL/ELT processes. Experience with version control systems such as Git. Education Required Bachelor's Degree Listed salary ranges may vary based on experience, qualifications, and local market. Also, some positions may include bonuses or other incentives Stefanini takes pride in hiring top talent and developing relationships with our future employees. Our talent acquisition teams will never make an offer of employment without having a phone conversation with you. Those face-to-face conversations will involve a description of the job for which you have applied. We will also speak with you about the process, including interviews and job offers. About Stefanini Group The Stefanini Group is a global provider of offshore, onshore and near shore outsourcing, IT digital consulting, systems integration, application, and strategic staffing services to Fortune 1000 enterprises around the world. Our presence is in countries like the Americas, Europe, Africa, and Asia, and more than four hundred clients across a broad spectrum of markets, including financial services, manufacturing, telecommunications, chemical services, technology, public sector, and utilities. Stefanini is a CMM level 5, IT consulting company with a global presence. We are a CMM Level 5 company.

Position Title: Manager - Advanced Analytics Description: Summary Statement: Lead the information technology aspects of advanced analytics projects and the machine learning (ML) environment. This critical role is responsible for delivering and supporting multiple AI/ML and data science projects across the enterprise. You will assess and select technologies and tools to support advanced analytics projects, and be a member of the Data & Emerging Digital Technologies team driving execution of data and digital initiatives. Collaborate closely with business and IT stakeholders across the organization, understand industry best practices, and drive the architecture and implementation of AI/ML projects. Key Responsibilities: • Evangelize artificial intelligence and machine learning across the organization to solve business problems and optimize processes. • Operationalize and support various Machine Learning models, ensuring accuracy and managing the cost of AI/ML operations. • Manage a team of machine learning engineers. • Work with analytics leaders, data analysts, and data scientists in various business groups (Marketing, Maintenance, Pricing, Finance) and IT groups (Data Engineering, Data Platform Teams, Product Managers, Cloud Engineering). • Responsible for talent management (recruiting, onboarding, career development) in the AI/ML Ops area. Responsibilities: • Collaborate with stakeholder groups and partners at mid to Sr. Management level to build and execute AI/ML roadmaps. • Manage and lead enterprise-wide projects and initiatives concurrently, assigned from client group leadership and other IT departments. • Lead and manage a team of machine learning engineers and AI/ML Ops administrators to support various AI/ML projects (Predictive Analytics, Prescriptive Analytics, Computer Vision, Gen AI). • Stay updated on best practices in AI/ML, AI/ML Ops, and Model API Management to leverage them within the organization, execute on MLOps Roadmap maturity. • Ensure applications and environments are available and supported as per agreed SLAs. • Enforce best practices and compliance with AI Governance principles. • Follow IT practices in security, licensing, source code management, incident management, and architectural standards. • Delegate and assign tasks to onshore and offshore technical resources. Regularly review project requirements, deliverables, and quality with partner leadership and onsite team members. • Ensure associates lead project scope development and options analysis to recommend technical solutions meeting customer needs. • Follow the Penske Development Process (PDP) and ensure timely capture of all information for relevant metrics generation, including attending tollgates, change control, and deployment discussions. • Work with Program/Project managers to ensure project completion and implementation on time, adhering to department quality standards while ensuring effective cost management. • Identify skill gaps within teams and develop plans to bridge them. • Foster collaboration among associates and within work groups. • Use dashboards and metrics to prioritize work and ensure project milestones are met. Qualifications: • Bachelor's degree in Computer Science, Information Systems, or equivalent experience. • 3+ years of leadership experience leading machine learning engineers. • 3 - 5 years of large enterprise-wide program/project management experience. • 2+ years' experience with cloud platforms, preferably AWS. • Strong experience with Agile/MLOps approaches or methodologies. • Strong Technical Project Management experience. • Strong knowledge of AI/ML using Python, data science tools and methodologies, advanced quantitative modeling, statistical analysis, parametric and non-parametric statistical modeling and techniques, API Management, Micro-services, and Cloud (preferably AWS), and experience operationalizing predictive or prescriptive models. • Working knowledge of one or more Machine Learning Platforms. • Expertise in leading the architecture, design, and implementation of AI/ML-based technical solutions. • Strong experience presenting to mid & Senior Management. Ability to explain complex AI/ML topics in simple terms to various stakeholders. • Experience working with business leadership to establish a project/program application development roadmap. • Experience working with various IT teams to build and implement a scalable architecture for relevant software solutions. • Demonstrated ability to break technical solutions into logical units and show information or data flow. • Full fluency and expert-level knowledge in systems/languages applicable to the role. • Full understanding of system development lifecycle, methodologies, and standards. • Working knowledge of Generative AI and Agentic solutions preferred. • Green Belt, Black Belt, Lean, or PMP certification preferred. Physical Requirements • The physical demands described here are representative of those that must be met by an associate to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. • The associate must regularly lift and /or move up to 25lbs/12kg. • Specific vision abilities required by this job include Close vision, Distance vision, Peripheral vision, Depth perception and Ability to adjust focus. • While performing the duties of this Job, the associate is regularly required to stand; walk; sit and talk or hear. The associate is frequently required to use hands to finger, handle, or feel and reach with hands and arms. Penske is an Equal Opportunity Employer. About Penske Truck Leasing/Transportation Solutions Penske Truck Leasing/Transportation Solutions is a premier global transportation provider that delivers essential and innovative transportation, logistics and technology services to help companies and people move forward. With headquarters in Reading, PA, Penske and its associates are driven by a dedication to excellence and a commitment to customer success. Visit Go Penske to learn more. Job Category: Information Technology Job Function: Business Intelligence Job Family: Analytics & Intelligence Address: 100 Gundy Drive Primary Location: US-PA-Reading Employer: Penske Truck Leasing Co., L.P. Req ID: Requirements PI

Senior Lead AI Engineer (Gen AI Platform Services, Agentic AI) Overview: At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 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 4 years of experience developing AI and ML algorithms or technologies At least 6 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 7 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, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Sr. Lead AI Engineer New York, NY: $250,800 - $286,200 for Sr. Lead AI Engineer Cambridge, MA: $229,900 - $262,400 for Sr. Lead AI Engineer San Francisco, CA: $250,800 - $286,200 for Sr. Lead AI Engineer San Jose, CA: $250,800 - $286,200 for Sr. Lead AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

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

Senior Lead AI Engineer (Gen AI Platform Services, Agentic AI) Overview: At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 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 4 years of experience developing AI and ML algorithms or technologies At least 6 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 7 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, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Sr. Lead AI Engineer New York, NY: $250,800 - $286,200 for Sr. Lead AI Engineer Cambridge, MA: $229,900 - $262,400 for Sr. Lead AI Engineer San Francisco, CA: $250,800 - $286,200 for Sr. Lead AI Engineer San Jose, CA: $250,800 - $286,200 for Sr. Lead 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. Distinguished Machine Learning Engineer (Remote-Eligible) Overview: 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 Consumer Engagement Platform organization at Capital One empowers rapid financial product innovation at scale and delivers developer joy, for all Capital One's consumer products and organizations, by providing well-managed, self-service, experimentation-driven, and personalized product development vehicles. Hyper Personalization org is building the intelligence and infrastructure that will enable Capital One to deliver truly individualized, real-time customer experiences at scale - turning every channel into a context-aware decisioning surface, from home feeds to marketing and servicing messages. The org's mission is to move Capital One to deliver always-on, cohort-of-one personalization, powered by resilient data foundations, production-grade ML and GenAI systems, and low-latency application platforms that make it easy for teams across the company to experiment, innovate, and serve the right experience to every customer at the right moment. What you'll do in the role: Define and drive technical strategy and roadmap for our Personalization Platform that powers real-time, personalized product experiences and multi-channel targeted user messaging across all Capital One products and services. Partner cross-functionally with Product, Data science, Cloud infrastructure, and Machine learning platform teams to align on and co-develop the advanced recommendation systems and algorithms serving our Capital One users. Develop and maintain a flexible, scalable rules engine to enable business-driven personalization logic, allowing dynamic configuration of user segmentation, targeting rules, and real-time decisioning while integrating seamlessly with ML-driven recommendations. Design, build and maintain robust ML infrastructure and pipelines to support end-to-end workflows including feature extraction, model training, testing, guardrails, model evaluation, deployment, and both real-time and batch inference - ensuring high performance, scalability, and reliability. Architect low-latency, event-driven systems for enabling real-time dynamic personalization and decisioning based on streaming data, user behavior, and contextual signals. Drive the evolution of MLOps practices by building automated metrics-backed deployment workflows, integration validation and testing systems, and scalable monitoring & observability. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Provide organizational technical leadership to influence architecture, engineering standards, cross-team strategies, mentoring engineers and driving organization wide platform innovation. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree At least 10 years of experience designing and building data-intensive solutions using distributed computing At least 7 years of experience programming in C, C++, Python, or Scala At least 4 years of experience with the full ML development lifecycle using modern technology in a business critical setting Preferred Qualifications: 8+ years of experience deploying scalable, responsible AI solutions on major cloud platforms (AWS, GCP, Azure); Master's or PhD in Computer Science or a relevant technical field. 5+ years of proven expertise in designing, implementing and scaling personalization platform and recommendation systems serving one or more areas of Feed Personalization/Ads Ranking/Targeted Marketing Messaging. 5+ years of strong proficiency in Python, Java, C++, or Golang; hands-on experience with ML frameworks (PyTorch, TensorFlow) and orchestration tools (Databricks, Airflow, Kubeflow). 5+ years of experience developing and applying state-of-the-art techniques for optimizing training and inference systems to improve hardware utilization, latency, throughput, and cost. 5+ years of deep expertise in cloud-native engineering, containerization (Docker, Kubernetes), and automated CI/CD deployment. Passion for staying on top 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 Proven leadership in driving platform strategy, fostering cross-functional collaboration, and influencing technical direction across the company. Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $286,200 - $326,700 for Sr Distinguished Machine Learning Engineer McLean, VA: $314,800 - $359,300 for Sr Distinguished Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to . click apply for full job details