Applied AI/ML Scientist Intern: Shipping & Packing

Faire; San Francisco (CA); Hybrid; USD 88,000 - 118,000; Part time

Benefits offered by this job

Paid internship

Flexible start dates

Hybrid work arrangement

Extensions possible

Job summary

Faire is seeking a talented Applied AI/ML intern for its Shipping and Fulfillment team in San Francisco. You will work on models predicting packing, optimize costs, and infer product attributes from images and text.

You'll prototype, train, and benchmark models offline, then push the best approaches to live traffic, collaborating with scientists and engineers. This paid winter internship runs 12–14 weeks starting Jan 2027.

Qualifications

• Currently enrolled in or recently graduated from a Master’s or PhD program in Computer Science, Machine Learning, Statistics, Electrical Engineering, or a related technical field
• Hands‑on experience building deep learning models (e.g., PyTorch), ideally with images, text, or both, including fine‑tuning pre‑trained models or working with embeddings
• Familiarity with gradient‑boosted trees and other tabular ML methods
• Strong Python and SQL
• Ability to read research papers and turn promising ideas into working code
• Solid grounding in statistics and model evaluation, including benchmarking against strong baselines and estimating uncertainty
• Comfort working with noisy or incomplete real‑world data
• A genuine enthusiasm for tackling ambiguous problems and learning new tools and techniques

Responsibilities

• Own a focused AI/ML project in shipping and fulfillment.
• Prototype and train models offline, benchmarking against current methods.
• Build out the strongest approach into a working implementation.
• Work with Applied Scientists and ML Engineers to test it against live traffic.
• Present findings and recommendations to the team

Skills

Deep learning

Python

SQL

Reading papers

PyTorch

Education

Master’s or PhD in CS/ML/Statistics/EE

Tools

PyTorch

Job description

Faire is seeking a talented Applied AI/ML intern for its Shipping and Fulfillment team in San Francisco. You will work on models predicting packing, optimize costs, and infer product attributes from images and text.

You'll prototype, train, and benchmark models offline, then push the best approaches to live traffic, collaborating with scientists and engineers. This paid winter internship runs 12–14 weeks starting Jan 2027.