Overview
Locations: VA - McLean, United States of America, McLean, VirginiaSr Distinguished Engineer, Generative AI Systems - (Remote- Eligible)
Sr Distinguished Engineer, Generative AI Systems
Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of generative AI that few other organizations can. We are committed to building world-class applied science and platform engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance generative AI infrastructure. At Capital One, you will help bring the transformative power of generative AI to reimagine how we serve our customers and businesses who have come to love the products and services we build.
We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundation of our Generative AI platform and the eco-system of services. You will work on a wide range of initiatives, whether that’s designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our platform while helping to design and implement key services. Examples of projects you will work on include:
Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries.
Design and build infrastructure for serving large ML models, in our public cloud.
Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud.
Design and implement benchmarks to measure the performance of software systems within a Generative AI Platform and make recommendations on technology selection
Develop applications that leverage LLMs and FMs, e.g. conversational AI.
Design and implement platform capabilities to support MLOps for foundation models.
Capital One is open to hiring a Remote Employee for this opportunity
Basic Qualifications:
Bachelor's degree in Computer Science, Computer Engineering or a technical field
At least 9 years of experience designing and building distributed computing/HPC and large-scale ML systems
At least 6 years of experience developing AI/ML algorithms in Python or C/C++
At least 3 years of experience with the full ML development lifecycle using open-source AI/ML frameworks and public cloud.
Preferred Qualifications:
Master’s degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques.
Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP.
Experience architecting cloud systems for security, availability, performance, scalability, and cost.
Experience with delivering very large models through the MLOps life cycle from exploration to serving.
Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking.
Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc.
Experience with GenAI technology stack including frameworks for prompt engineering, guardrails for GenAI applications, and LLM fine tuning.
Experience working with VectorDBs and other data infrastructure required to efficiently support Generative AI training pipelines and production applications.
Experience training and maintaining large language models.
Authored research publications in top peer-reviewed conferences, or industry-recognized open-source contributions in the space of neural networks, distributed training and SysML.
At this time, Capital One will not sponsor a new 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.
New York City (Hybrid On-Site): $315,100 - $359,700 for Sr Distinguished Machine Learning EngineerSan Francisco, California (Hybrid On-Site): $333,900 - $381,000 for Sr Distinguished Machine Learning EngineerRemote (Regardless of Location): $267,100 - $304,800 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 theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
No agencies please. Capital One is an Equal Opportunity Employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex, race, color, age, national origin, religion, physical and mental disability, genetic information, marital status, sexual orientation, gender identity/assignment, citizenship, pregnancy or maternity, protected veteran status, or any other status prohibited by applicable national, federal, state or local law. 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 4901-4920; 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 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. 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 Careers@capitalone.com
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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).