Machine Learning Engineer

Lantern • San Francisco, CA

20d • $200,000 - $200,000 • Onsite

About The Position

Lantern is hiring a Machine Learning Engineer to scale the production ML platform behind its AI-powered purchasing recommendations for wholesale distributors. The role owns the platform end to end, including operational-data ingestion, model training, inference, and production monitoring. The focus is making these workflows scalable, repeatable, observable, and easy to operate across hundreds of customers. This is a high-ownership role on a small team, working directly with the CTO to deliver systems customers rely on.

Requirements

• 4–6 years as an ML or Software Engineer building ML systems in production.
• Strong software engineering fundamentals and ability to write clean, maintainable, production-grade code.
• Experience building and scaling ML training and inference pipelines, ideally multi-tenant or per-customer.
• Hands-on experience with Python, cloud infrastructure (AWS or GCP), and orchestration tools such as Airflow, Kubeflow, or similar.
• Comfort working with messy, real-world data.
• BS/MS in Computer Science or a related technical field.

Nice To Haves

• Supply chain, logistics, demand forecasting, or operations-adjacent experience.
• Experience with time-series forecasting frameworks and traditional ML tools such as XGBoost, LightGBM, or scikit-learn.
• Prior early-stage startup experience, including wearing multiple hats.

Responsibilities

• Own and scale the ML and data pipelines that power customer recommendations.
• Build reusable infrastructure for data ingestion, feature generation, model training, validation, and output.
• Improve pipeline performance, reliability, and observability as the company scales across more customers.
• Build systems that detect data-quality issues, pipeline failures, and unexpected outputs before they reach customers.
• Turn customer-specific workflows into repeatable, configuration-driven systems and help shape platform architecture.

Benefits

• Competitive compensation: approximately $200K base plus meaningful equity.
• Office in San Francisco with a tight-knit founding team.
• High-impact, founding-era role at a hypergrowth startup.
• Opportunity to own the ML platform that drives customer P&L and make a positive impact across the supply chain and economy.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level