Applied ML Intern: Build Production-Ready Models

Carrerlift; New York (NY); On-site; USD 150,000 - 170,000; Full time

Benefits offered by this job

Housing stipend

Apple MacBook provided

Catered weekday lunches (NYC office)

Weekly coffee stipend

Job summary

Ramp’s Applied Science internship offers a hands-on role on an integrated team, owning an ML project end-to-end. You’ll work with engineers, product managers and business stakeholders to turn complex requirements into scalable ML solutions that ship production code and create measurable value for Ramp and customers.

You will explore data, engineer features, train models, benchmark, deploy and monitor, and apply AI/LLMs to expand customer-facing capabilities while collaborating with product teams.

Qualifications

• Pursuing degree with expected graduation Dec 2027–Dec 2029.
• Strong foundations in ML math, statistics, probability and optimization.
• Interest or experience applying AI/LLMs to practical problems.
• Proficient in Python with pandas, scikit-learn, NumPy and PyTorch.
• Knowledge of SQL and warehouses like Snowflake, BigQuery, Redshift or ClickHouse.
• Experience preparing datasets and building ML models.
• Strong communication to explain complex ideas and tell data-driven narratives.
• Comfortable with ambiguity and shipping solutions.

Responsibilities

• Manage the full ML lifecycle from data exploration to deployment and monitoring.
• Apply modern LLMs to create customer-facing capabilities.
• Select techniques such as deep learning, gradient boosting, and causal inference.
• Measure results with A/B testing and other experiments.
• Partner with product/business teams to translate model outputs into strategy and user features.

Skills

Python

SQL

Pandas

scikit-learn

NumPy

PyTorch

Communication

Education

Pursuing B.S./M.S./Ph.D. in Data Science, CS, Math, Physics, Economics, Statistics

Tools

Snowflake

BigQuery

Redshift

ClickHouse

Airflow

Dagster

Prefect

Metaflow

Git

Job description

Ramp’s Applied Science internship offers a hands-on role on an integrated team, owning an ML project end-to-end. You’ll work with engineers, product managers and business stakeholders to turn complex requirements into scalable ML solutions that ship production code and create measurable value for Ramp and customers.

You will explore data, engineer features, train models, benchmark, deploy and monitor, and apply AI/LLMs to expand customer-facing capabilities while collaborating with product teams.