Top Tech Jobs & Startup Jobs

Own product strategy for assigned domains, translating customer and business needs into requirements, workflows, priorities, and success measures. Partner with business leaders, Product Managers, and Engineering throughout the product lifecycle. Lead cross-functional initiatives, resolve dependencies, assess opportunities and tradeoffs, support portfolio planning, and maintain alignment from problem definition through delivery and business readiness.

Design, develop, and deploy scalable production ML systems for ad ranking, recommendation, and advertiser optimization; analyze large-scale data, own the ML lifecycle (feature engineering, training, evaluation, deployment, monitoring), improve system metrics (relevance, revenue, latency), apply deep learning and GenAI, and mentor junior engineers.

As a Staff ML Engineer, lead the development of machine learning systems for advertising, drive strategic data decisions, optimize system performance, and mentor engineers.

Leads global internal communications for Finance, Legal, and Growth, advising the CFO, CLO, and Chief Growth Officer. Develops strategic narratives, executive communications, change-management and crisis communications, global alignment, employee engagement events, communication playbooks, and measurement strategies. Partners with Corporate Communications, Marketing, Investor Relations, HR, Finance, and Legal to align internal messaging with corporate strategy, financial reporting, regulatory initiatives, and brand positioning.

Provides technical leadership for machine learning initiatives across eBay Ads and marketplace discovery. Designs, builds, and operates scalable production ML and backend systems for sponsored search, recommendations, ranking, retrieval, personalization, and GenAI. Partners with researchers to productionize algorithms, promotes engineering best practices, mentors engineers, and drives customer and business impact through experimentation, monitoring, alerting, and incident response.

Build and operate scalable machine learning platforms, data pipelines, MLOps workflows, APIs, and production services for eBay Ads. Develop and serve traditional and generative AI models supporting search, recommendations, ranking, retrieval, and personalization. Collaborate with researchers and engineers to productionize algorithms, improve reliability and performance, resolve incidents, and mentor team members.

Build and operate scalable backend and machine learning systems for sponsored search, recommendations, ranking, retrieval, personalization, and generative AI. Develop MLOps, data, training, validation, serving, monitoring, and CI/CD pipelines; optimize low-latency model services and APIs; productionize research prototypes; resolve reliability issues; and mentor engineers. Collaborate with applied researchers, product managers, and engineering teams to deliver production-ready ML capabilities at global ecommerce scale.

Build and operate scalable machine learning platforms, data pipelines, APIs, and MLOps systems for eBay Ads. Develop and productionize traditional and generative AI models supporting search, recommendations, ranking, retrieval, and personalization. Own model training, deployment, monitoring, and reliability in 24/7 environments. Collaborate with researchers, product managers, and engineers to convert prototypes into low-latency production systems, while contributing to software engineering best practices and mentoring teammates.

Lead and grow a team of applied researchers and engineers to build and operate production AI/ML systems (NLP, LLMs, recommender systems) at scale, set technical direction, partner cross-functionally, and drive measurable business and customer impact.

Build and productionize multi-agent systems and agentic workflows for personalized e-commerce recommendations. Design agent coordination, communication, planning, evaluation, tool use, safety controls, and orchestration techniques. Address latency, cost, and reliability challenges at eBay scale while collaborating with researchers, engineers, product, design, and analytics teams. Use large multimodal datasets and A/B testing to improve marketplace outcomes.