Technical Lead Manager, MLOps

About Veho Veho’s mission is to power the future of commerce by making shopping, shipping and returns seamless for everyone. We build a modern, end‑to‑end logistics infrastructure designed entirely for the ever‑evolving needs of ecommerce brands and everyday consumers. Powered by next‑generation technology and a vertically integrated supply chain, Veho gives brands and their customers unprecedented control over deliveries and removes the pain from the ecommerce post‑purchase experience. We make delivery the extension of the brand and leverage it to create deeper loyalty and trust between brands and their customers, driving customer retention and lifetime value. Our rapidly growing client list includes leading consumer brands like Hello Fresh, Zara, Macy’s, Sephora, and more. To truly build an iconic company, we strongly believe that our people and values must be aligned with our mission. As such, we take pride in our championship team, merit‑based culture. We seek team players who want to compete, win, make an impact and build a legacy, and we reward performance and impact players with generous equity and incredible career growth opportunities. About The Role Veho’s Data Science team is core to Veho’s ability to deliver millions of packages by creating the systems that drive forecasting, network orchestration, pricing, and routing decisions. The Machine Learning Operations team drives the foundation of these systems by partnering with data scientists to create well‑designed, stable, and performant systems. As the Technical Lead Manager, you own our Data Science platform and 1–2 year roadmap for creating a sophisticated and stable platform that keeps up with Veho’s rapid growth. You and your team embed into science projects so engineering quality is built in from day one, and create templates to get new systems up and running quickly. You push the AI‑assisted development agenda and are a thought leader on leveraging AI to improve development velocity. You manage the Machine Learning Operations team and contribute significantly by writing code, reviewing designs, and setting the technical bar. You partner closely with our Agentic Developer Experience and Builder Experience teams. A Great Candidate Expert in ML infrastructure and delivering impactful models. Collaborates closely with the Data Science team, keeping business value centered. Has a bias for action, balancing short‑term impact with long‑term vision. Applies ML/MLOps knowledge to propose new patterns, tools, and approaches to improve the team’s models. Drives team velocity by developing careers, hiring talent, and adopting AI as core. What You’ll Do Lead and grow a team of four engineers across ML infrastructure, ML operations, and embedded data science. Improve the internal ML platform: standardize and enhance infrastructure, and how data‑science services are created, deployed, and operated. Set the roadmap for improving Machine Learning and Operations Research infrastructure. Embed engineers into major science initiatives (forecasting, network orchestration, pricing) ensuring technical soundness and shared lessons. Drive AI usage across DS by collaborating with the Agentic Developer Experience team; set standards, introduce patterns, and promote AI adoption in data‑science workflows. Participate in the on‑call rotation for data‑science production systems. What You Bring Bachelor’s degree with at least 6 years of experience in Machine Learning Engineering, or Master’s degree with at least 4 years. Experience with ML platform components: training/serving infrastructure, feature stores, orchestration, monitoring, deployment pipelines. Experience managing high‑velocity ML/Platform teams in smaller scale companies. Experience driving AI/agentic tooling adoption within an organization. Hands‑on experience with open‑source tooling for large‑scale ML (e.g., Ray, Flink, Feast). Strong knowledge of cloud‑based data engineering and data‑science tools (AWS preferred) and data warehouses (Redshift, Databricks, Snowflake). Strong proficiency in Python. Interest in building systems in a supply‑chain setting to enable physical supply‑chain to run like clockwork. All California applicants please reference our California Applicant Privacy Notice located here. #J-18808-Ljbffr Veho