Distinguished AI Engineer
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Role details
Tech stack
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Requirements
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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.
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Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production.
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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.
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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.
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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
At least 15 years of experience in software engineering or solution architecture
At least 10 years of experience designing and building data intensive solutions using distributed computing
At least 8 years of experience programming with Python, Go, or Java
At least 6 years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
Preferred Qualifications
Master’s Degree or PhD in Computer Science, Electrical Engineering, Mathematics
5+ years of experience building, scaling, and optimizing ML systems
5+ years of experience with data gathering and preparation for ML models
10+ years of experience developing performant, resilient and maintainable code
Experience developing and deploying ML solutions in a public cloud such as AWS, Azure or Google Cloud Platform
5+ years of experience with distributed file systems or multi-node database paradigms
Contributed to open source ML software
Authored/co-authored a paper on a ML technique, model or proof of concept
5+ years of experience building production-ready data pipelines that feed ML models
Experience in designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance
5+ years of experience in ML Ops either using open source tools like ML Flow or commercial tools
2+ Experience in developing applications using Generative AI i.e open source or commercial LLMs
About the company
At Capital One India , 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:
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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.
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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.
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Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.
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Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems.
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Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.
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