Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

The Product Manager at Stord will optimize warehouse operations by translating operational needs into product requirements, collaborating with internal teams, and implementing efficient WMS solutions while spending significant time onsite to gather feedback.

Partner with sales to design and demo tailored OMS/WMS and fulfillment solutions, lead discovery, document technical requirements, respond to RFPs, and hand off implementations while advising product teams.

The Parcel GTM Manager directs Go-To-Market strategy for Stord's Customer Experience and M&A lines, leading a team of analysts to manage pricing, margin optimization, network analytics, and process engineering, ensuring seamless integration for clients and achieving revenue goals.

The Staff Software Engineer will lead technical initiatives, drive quality code, mentor engineers, and work on scalable systems in a high-impact team environment.

Lead end-to-end experimentation pipeline for Stord Labs, coordinating robotics, AI, vendors, engineering, and operations to validate and scale logistics innovations into production pilots and enterprise rollouts, develop deployment playbooks, and manage co-funded customer pilots and executive demonstrations.

The Data Engineer will design and maintain data pipelines, enhance the data warehouse, support machine learning applications, and collaborate with various teams to leverage data effectively.

Seeking a Senior Elixir Engineer to develop scalable systems and contribute to technical decisions within product groups, focusing on Elixir and cloud technologies.

The Senior Software Engineer will develop robust systems using Elixir, collaborate on product strategy, and ensure system performance and reliability.

The Staff Software Engineer will lead technical excellence, design scalable systems, mentor engineers, and drive innovation in a cross-functional team.

Senior individual contributor owning complex end-to-end ML problems for supply chain and consumer applications. Build and deploy predictive models (demand forecasting, delivery ETA, recommendations), embed with engineering teams, define MLOps standards, and advise leadership on data science strategy and investments.