Onsite AI/ML & Data Eng Intern — Build Real Systems

Regeneron Pharmaceuticals, Inc (USA); Village of Tarrytown (NY); On-site; USD 25,000 - 70,000; Full time

Benefits offered by this job

Annual bonuses

Equity awards

Pension or retirement benefits

401(k) company match

Health and wellness programs

Fitness centers

Insurance benefits

Paid time off

Family support benefits

Job summary

Regeneron Pharmaceuticals, Inc. offers full-time internship and co-op positions across multiple locations, including Tarrytown, Warren, Armonk, Cambridge, and Sleepy Hollow. Most roles are on-site with some hybrid opportunities.

Internship pay is hourly, determined by education level and degree program, at $17.90–$50.90 per hour. You will build and test AI solutions, work on AI agents, NLP, data pipelines and ML prompts, and collaborate with scientists and business teams.

Qualifications

• Demonstrated leadership in campus activities, clubs, sports or work is preferred.
• Must be enrolled in or accepted to an academic program pursuing an Undergraduate or Graduate degree and returning to school after the position.
• Cumulative GPA of 3.0 or higher preferred.

Responsibilities

• Build and test AI solutions used on real systems; projects may include AI agents and LLM-powered apps.
• Mine text with NLP; build and modernize data pipelines and semantic data models.
• Collaborate with scientists and business teams; use Python, SQL, and AI tooling with proper governance.

Skills

Leadership

Campus activities leadership

Team collaboration

Education

Undergraduate or Graduate degree program

Tools

Python

SQL

ML packages

Job description

Regeneron Pharmaceuticals, Inc. offers full-time internship and co-op positions across multiple locations, including Tarrytown, Warren, Armonk, Cambridge, and Sleepy Hollow. Most roles are on-site with some hybrid opportunities.

Internship pay is hourly, determined by education level and degree program, at $17.90–$50.90 per hour. You will build and test AI solutions, work on AI agents, NLP, data pipelines and ML prompts, and collaborate with scientists and business teams.