Top AI & Machine Learning Jobs

As a Lead AI Engineer, you will develop and support AI products, enhance system performance, and collaborate across teams to innovate AI solutions for Capital One.

Lead the design, development, and deployment of AI software components while partnering with engineers and scientists to deliver innovative AI solutions at Capital One.

The role involves leading a team to develop machine learning models for Travel Intelligence, focusing on the Hotels domain. Responsibilities include collaborating with cross-functional teams, leveraging technologies for data analysis, and delivering products that enhance customer experiences.

Lead AI Engineer responsible for developing AI-powered products, optimizing large language model inference, and collaborating across teams to enhance customer interactions and business value.

The Senior Lead Machine Learning Engineer will design, implement, and scale ML applications, ensuring performance and high availability while collaborating with cross-functional teams.

The Senior Manager, Data Science will lead a team to assess and mitigate model risks, develop machine learning models, and enhance decision-making processes across various business domains in Capital One's Model Risk Office.

Lead AI Engineer responsible for designing and developing AI-powered products, utilizing ML algorithms, and optimizing large-scale AI systems. Collaborate with cross-functional teams to enhance customer experience and drive AI initiatives at Capital One.

Lead and grow an AI engineering organization building foundation-model training and LLM-powered production systems. Own design, deployment, optimization, evaluation, governance, and observability of scalable AI platforms; make build-vs-buy decisions across open source and SaaS AI technologies; drive technical vision and mentor engineering teams to deliver responsible, high-performance AI capabilities.

Build, validate, and implement machine learning models on large, multi-source datasets using Python, cloud, and big-data tools. Partner with engineers and product managers to deliver analytics products, translate technical results into business impact, and apply statistical methods (classification, clustering, time series, deep learning, sentiment analysis).

Lead end-to-end development, deployment, and monitoring of AML machine learning models; own model governance, audit and regulatory responses; set strategy, product/marketing analytics, credit risk modeling, and execute cross-functional initiatives while coaching 1-2 analysts.