
10.000+ funcionários
🏦 Bancário
💳 Fintech
💸 Finanças
💰 Post-IPO Equity em 2023-05
Banking • Fintech • Finance
A Capital One é uma empresa de serviços financeiros especializada em cartões de crédito, bancos e empréstimos. Comprometida com a inovação, a Capital One combina tecnologia e estratégias baseadas em dados para aprimorar a experiência do cliente e melhorar seus serviços bancários. A empresa também enfatiza a diversidade, inclusão e uma cultura de trabalho colaborativa, enquanto oferece uma ampla gama de oportunidades de emprego em várias áreas, incluindo finanças, tecnologia e atendimento ao cliente.
🕒 Setembro 23
🏄 California, New York, +2 estados a mais – Remoto
💵 $286.200 - $392.000 / ano
⏰ Tempo Integral
🟠 Sênior
🤖 Engenheiro de IA
🦅 Patrocina Visto H1B
👻 Score fantasma 0%
🗣️🇺🇸🇬🇧 Inglês obrigatório
Melhore suas chances de conseguir uma entrevista verificando sua pontuação de currículo antes de se candidatar.

10.000+ funcionários
🏦 Bancário
💳 Fintech
💸 Finanças
💰 Post-IPO Equity em 2023-05
Banking • Fintech • Finance
A Capital One é uma empresa de serviços financeiros especializada em cartões de crédito, bancos e empréstimos. Comprometida com a inovação, a Capital One combina tecnologia e estratégias baseadas em dados para aprimorar a experiência do cliente e melhorar seus serviços bancários. A empresa também enfatiza a diversidade, inclusão e uma cultura de trabalho colaborativa, enquanto oferece uma ampla gama de oportunidades de emprego em várias áreas, incluindo finanças, tecnologia e atendimento ao cliente.
• Partner with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products • Design, develop, test, deploy, and support AI software components including foundation model training, LLM inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability • Leverage open-source and SaaS AI technologies such as AWS Ultraclusters, Hugging Face, VectorDBs, and PyTorch • Invent and introduce state-of-the-art foundation model optimization techniques to improve scalability, cost, latency, and throughput • Contribute to the technical vision and long-term roadmap of foundational AI systems at Capital One • Define and steer the technical AI architecture vision, integrating applied research breakthroughs into reliable, scalable production ecosystems • Lead the establishment of AI performance, safety, and transparency standards for company-wide model development and deployment • Drive multi-year platform initiatives unifying data, compute, and model lifecycle management under an enterprise AI architecture • Mentor senior technical leaders across research, data, and engineering disciplines
• Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies; or a Master's degree in these fields plus at least 8 years of such experience • At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java • Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy • 9 years of experience deploying scalable and responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or equivalent private cloud • Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems • Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level • Experience developing AI and ML algorithms or technologies using Python, C++, C#, Java, CUDA, or Golang • Experience developing and applying state-of-the-art techniques for optimizing training and inference software • Experience building agentic AI systems and workflows • Recognized industry leadership in applied AI or machine learning infrastructure through patents, publications, or open-source leadership • Experience designing long-term AI infrastructure strategies while balancing cost, scale, ethics and regulatory compliance • Experience driving organization-wide adoption of AI safety, alignment and governance standards • Proven ability to shape R&D investment strategy • Experience right-sizing models, instance counts, and hardware types • Qualified applicants may be eligible for employment authorization sponsorship
• Performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI) • Comprehensive, competitive, and inclusive health, financial and other benefits supporting total well-being • Reasonable accommodations for applicants who require them
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