Lantern - Founding AI Engineer

Why 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. Were 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 wont be polishing dashboards - theyll steer billions in working capital.

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

• End-to-end machine learning ownership. As founding engineer youll 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.

About Us

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

The Role

As Lanterns Founding AI Engineer youll be the fifth person on the team and wear many hats. Youll partner directly with the founders to design data pipelines build and deploy ML models and stand up MLOps that scales across customers. This isnt just an engineering job - its a chance to shape the product architecture and company.

What Youll Do

• 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

Who You Are

Must-Have:

• 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

Bonus Points:

• 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

What We Offer

• 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