NYC Staffing
Senior 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. 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. Proficiency in developing robust, high-performing systems, coupled with the skill to pinpoint performance limitations within the ML pipeline for model deployment, training, and oversight. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, Spark, Kubeflow 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: Loves to build systems, takes pride in the quality of their work, and shares our passion to do the right thing. They want to work on problems that will help change banking for good. Strong documentation skills are essential; they should be adept at writing design documents and leading projects from start to finish. Experience with both software development lifecycles and machine learning lifecycles is a must for driving initiatives successfully. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. Adapt quickly and thrive on bringing clarity to big, undefined problems. They love asking questions and digging deep to uncover the root of problems and can articulate their findings concisely with clarity. Deeply technical. They possess a strong foundation in engineering and mathematics, and their expertise in hardware, software, and AI enable them to see and exploit optimization opportunities that others miss. 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, Engineering, or AI plus at least 6 years of experience developing AI and ML algorithms or technologies, or Master's degree 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 Expertise with Apache Spark for distributed data processing systems Experience in building ML workflows 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 Master's degree in Computer Science, Computer Engineering, or relevant technical field 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. Cambridge, MA: $225,400 - $257,200 for Sr. Lead AI Engineer Chicago, IL: $204,900 - $233,800 for Sr. Lead AI Engineer McLean, VA: $225,400 - $257,200 for Sr. Lead AI Engineer New York, NY: $245,900 - $280,600 for Sr. Lead AI Engineer Richmond, VA: $204,900 - $233,800 for Sr. Lead AI Engineer San Francisco, CA: $245,900 - $280,600 for Sr. Lead AI Engineer San Jose, CA: $245,900 - $280,600 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.
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. 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. Proficiency in developing robust, high-performing systems, coupled with the skill to pinpoint performance limitations within the ML pipeline for model deployment, training, and oversight. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, Spark, Kubeflow 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: Loves to build systems, takes pride in the quality of their work, and shares our passion to do the right thing. They want to work on problems that will help change banking for good. Strong documentation skills are essential; they should be adept at writing design documents and leading projects from start to finish. Experience with both software development lifecycles and machine learning lifecycles is a must for driving initiatives successfully. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. Adapt quickly and thrive on bringing clarity to big, undefined problems. They love asking questions and digging deep to uncover the root of problems and can articulate their findings concisely with clarity. Deeply technical. They possess a strong foundation in engineering and mathematics, and their expertise in hardware, software, and AI enable them to see and exploit optimization opportunities that others miss. 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, Engineering, or AI plus at least 6 years of experience developing AI and ML algorithms or technologies, or Master's degree 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 Expertise with Apache Spark for distributed data processing systems Experience in building ML workflows 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 Master's degree in Computer Science, Computer Engineering, or relevant technical field 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. Cambridge, MA: $225,400 - $257,200 for Sr. Lead AI Engineer Chicago, IL: $204,900 - $233,800 for Sr. Lead AI Engineer McLean, VA: $225,400 - $257,200 for Sr. Lead AI Engineer New York, NY: $245,900 - $280,600 for Sr. Lead AI Engineer Richmond, VA: $204,900 - $233,800 for Sr. Lead AI Engineer San Francisco, CA: $245,900 - $280,600 for Sr. Lead AI Engineer San Jose, CA: $245,900 - $280,600 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.