Top Tech Jobs & Startup Jobs

Lead the EASE Customer Experience design team to define strategy and deliver foundational web and mobile journeys. Own cross-functional collaboration, mentor designers, drive design systems, prototypes, research integration, and align design outcomes to business objectives and technical constraints.

Lead an analytics team to drive strategy for Accounts Payable and Expense Management. Translate customer, product, and financial data into insights, models, and experiments to inform product, pricing, marketing, and credit risk decisions. Partner cross-functionally to deliver business requirements, manage projects, mentor analysts, and measure impact to grow profitability and customer outcomes.

Lead operational governance for FPDS data pipelines: monitor 24/7 pipeline health and SLAs, manage incidents and stakeholder communications, drive GL reconciliations and audit compliance, partner with engineering to remediate defects, maintain data quality controls and provisioning agreements, and modernize operational frameworks to improve effectiveness.

Lead a team to deliver AI powered products, leveraging machine learning and NLP for customer applications, while collaborating with cross-functional teams.

The Senior Manager of Data Analysis will manage validation projects, assess analytical tool risks, and mentor junior staff while collaborating cross-functionally and enhancing analytical capabilities.

As an Applied Researcher I, you'll work with cross-functional teams to develop AI-powered products, engage in applied research, and build foundation models using various technologies.

The role involves leading cybersecurity product management by developing strategies, collaborating with stakeholders, managing projects, and mentoring teams to enhance security solutions.

The role involves partnering with a team to deliver AI products, utilizing various technologies and conducting applied research to enhance customer experiences leveraging AI.

Design, train, evaluate, and productionize machine learning models (including embeddings and foundation models) on large-scale data. Partner with product and engineering to run experiments, improve customer experiences, and deploy scalable solutions using Spark and AWS.

Lead design, development, deployment, and support of large-scale AI systems (foundation model training, LLM inference, similarity search, guardrails, evaluation, governance, observability). Partner cross-functionally, invent LLM optimization techniques, and contribute to technical vision and roadmap for foundational AI infrastructure.