Founding AI Engineer - Lantern

Supply chains power the world - but most distributors still rely on spreadsheets, gut instinct, and clunky ERP systems to make million-dollar purchasing decisions. We’re building Lantern, an AI-native purchasing copilot that helps wholesale distributors buy smarter.

• $8T market, zero modern AI. Wholesale distribution is massive, fragmented, and underserved. Your algorithms won’t be polishing dashboards - they’ll steer billions in working capital.

• Live pilots, real ARR. We already generate revenue with design partners who push our models in production every week. You’ll iterate on live feedback, not hypothetical use-cases.

• End-to-end machine learning ownership. As founding engineer, you’ll design data pipelines, train and deploy ML models, and watch your code drive purchase orders that cut stock-outs and slash excess inventory by 50%, giving millions of dollars of cash back to each customer.

• Proven tech + top-tier VC backing. Join founders with 10+ years of experience shipping large-scale ML products and ample funding from top-tier investors.

We’re a small, experienced founding team with a deep obsession for the problem. Between us, we’ve founded companies, shipped products at scale, and worked at places like Google, McKinsey, Stripe, and Walmart’s Applied AI Group. We studied at Stanford & IIT. Most importantly, we’re deeply aligned on speed, customer obsession, low-ego collaboration, and belief that a tiny team can transform an industry.

As Lantern’s Founding AI Engineer, you’ll be the fifth person on the team and wear many hats. You’ll partner directly with the founders to design data pipelines, build and deploy ML models, and stand up MLOps that scales across customers. This isn’t just an engineering job - it’s a chance to shape the product, architecture, and company.

• Own product velocity across the full ML stack - from cloud infra and data pipelines to model-serving endpoints and (lightweight) dashboards

• Ship ML features fast: prototype, demo to customers, iterate on feedback

• Scale our forecasting engine and data ingestion workflows across customers, with automated retraining and drift monitoring

• Design and build clean, scalable backends, APIs and inference services

• Collaborate on architecture, product direction, hiring, and culture

• Obsess over real-world outcomes: inventory turns, margin, cash flow

• Prior startup experience (or serious appetite for it)

• 2+ years relevant work experience

• Fluent in Python & SQL

• A track record of shipping ML systems to production – from feature engineering and training to serving, monitoring, and retraining

• Deep exposure to a modern cloud ML stack (we use GCP: BigQuery, Vertex AI, Cloud Composer)

• Strong systems design instincts and a bias for building pragmatic, scalable solutions

• High-agency, low-ego — you ship, you own, you care

• Based in the Bay Area — in office 5 days/week

• Hands-on with production MLOps (drift detection, model registries, feature stores, explainability)

• Experience working with time-series and unstructured data for forecasting/optimization

• Terraform & Kubernetes experience for infra-as-code and resilient deployments

• A history of mentoring early hires and contributing to culture

• Passion for supply chain, logistics, or the physical economy

• Highly competitive salary and equity commensurate with 100X performer

• Full health, dental, and vision insurance

• Visa support available

• Intangibles:

  • A true zero-to-one journey with direct line to customers, impact, and decisions

  • Mentorship from experienced founders and access to an elite investor network

  • Onsite collaboration that accelerates learning, velocity, and culture

  • The chance to help reinvent how an $8T industry operates