Machine Learning Engineer

Lantern; San Francisco (CA); On-site; USD 190,000 - 210,000; Full time

Benefits offered by this job

Equity

Office in San Francisco

Competitive salary

Job summary

Lantern is seeking a Machine Learning Engineer in San Francisco to scale the core ML platform behind our product. You will own the data ingestion, training pipelines, and the end-to-end ML workflow that generates customer recommendations used across all accounts.

We expect 4–6 years in ML or software roles, strong production-grade coding, and hands-on experience with Python, AWS or GCP, and orchestration tools like Airflow or Kubeflow. This is an in-office role with a tight-knit founding team.

Qualifications

• 4–6 years of experience building ML systems in production.
• Proficient in clean, maintainable, production-grade code.
• Experience with ML training and inference pipelines, ideally multi-tenant.

Responsibilities

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

Skills

ML systems in production

Python

Data pipelines

Cloud infrastructure

Airflow/Kubeflow

Software engineering

Multi-tenant ML

Education

BS/MS in Computer Science or related field

Tools

Airflow

Kubeflow

AWS

GCP

Job description

All roles Machine Learning Engineer Scale the core ML platform behind our product, owning pipelines that ingest data, train models, and generate recommendations that every customer relies on.

• In-office

Location San Francisco, CA

Experience 4–6 years

Compensation ~$200K base + equity

The role

We're hiring a Machine Learning Engineer to scale the core ML platform behind our product: the production systems that ingest operational data, train models, and generate recommendations. The central challenge is making these workflows scalable, repeatable, observable, and easy to operate across hundreds of customers. You'll own the platform end to end, from data ingestion through training pipelines to inference and monitoring in production. It's a high-ownership role on a small team, working directly with our CTO to ship systems every customer relies on.

What you'll do

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

What you bring

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

Nice to have

• Supply chain, logistics, demand forecasting, or operations-adjacent experience.
• Time-series forecasting frameworks and traditional ML tools (XGBoost, LightGBM, scikit-learn).
• Prior early‑stage startup experience where you wore multiple hats.

What you'll get

• A founding‑era, high‑impact role at a hyper growth startup.
• Own the ML platform that drives customer P&L on every account.
• Make a massive positive impact across our entire supply chain and economy.
• Competitive compensation: ~$200K base + meaningful equity.
• An office in San Francisco with a tight-knit founding team.

What we value

We hire strong engineers who build real systems, combining technical depth with pragmatic execution and a sense of ownership. Hard work, humility, customer obsession, and pride in a job well done. These are the values our customers live by, and the values we hire for.

About Lantern

Lantern is building the future of distribution. Billions of dollars sit tied up in stock, yet most distributors still buy on gut feel and spreadsheets. We partner with leading distributors to deliver precise, AI-powered purchasing recommendations that drive millions of dollars straight to the bottom line.