Top Tech Jobs & Startup Jobs in NYC, NY

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.

Lead Data Engineer designs, develops, tests, and supports cloud-based, distributed data solutions. Collaborates across Agile teams, mentors engineers, works with big data, streaming, NoSQL and data warehouse technologies, and ensures performant, well-tested code for customer-facing products.

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.

The role involves managing data science projects focused on travel intelligence, leveraging machine learning and data analytics to improve customer experiences.

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

As a Distinguished Engineer, you will lead cloud banking innovations, mentor teams, and design scalable fraud defenses using advanced technologies.

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.

Design, train, validate, and implement machine learning models using large-scale bureau and customer data. Partner with engineers and product managers to build data products, extract insights from numeric and textual data, and translate technical results into business impact using cloud and open-source tools.

Lead large-scale, technically complex cross-functional programs for enterprise platforms. Drive strategy, execution, architectural tradeoffs, dependency mitigation, platform consolidation, and grow TPM practice while collaborating with product, engineering, design, and data science teams.

Lead product efforts to build and expand operational data infrastructure and integrate machine learning into the Collections platform. Partner with enterprise platforms, business stakeholders, and risk teams to identify high-leverage opportunities, define product strategy, and deliver end-to-end solutions that improve segmentation and decisioning for card collections and recoveries.