Flagship Pioneering ML Internship

Description

The company is a scientific innovation company that builds new companies. It pairs entrepreneurial scientists with experienced company builders and raises the capital to back bold bets in human health, sustainability, technology and other areas.

AI is central to how the company creates businesses. It calls this approach polyintelligence, where human creativity and nature's intelligence work alongside artificial intelligence. Across the ecosystem, teams combine AI and machine learning with foundational science to move from idea to concept faster and to build AI-native companies that were not feasible before.

The company is looking for computational scientists and engineers with wide interests who have applied deep technical skills to scientific questions outside their usual territory. Building something from scratch is not the point. The aim is to spot where extending, changing or combining cutting-edge computational methods can unlock new abilities and address important problems. Strong candidates pair solid software engineering with openness to agentic development tools and practices, and have built machine learning models and workflows across several model types or scientific fields.

Responsibilities

• Work with Flagship origination teams and other ML scientists and engineers to explore what large leaps beyond current AI could make possible.
• Start by asking what if across many ideas, then work backwards to define what must be true for each one to happen.
• Compare options and their tradeoffs, including how much data is needed and where it could come from.
• Shape implementation and evaluation plans that tackle the real unknowns, not only the parts that are easy to measure.
• Once a project is defined, build, test and refine it, using Flagship's scalable GPU compute, data from the ecosystem and expertise across the teams.
• Build the benchmarks needed to measure what matters and to test your designs.
• Stay ready to change methods as you learn. Deliver complete answers to the backwards-planned questions, not just a model or a paper.

Requirements

• Deep technical experience applied to unfamiliar scientific problems.
• Solid software engineering fundamentals.
• Willingness to adopt agentic development tools and practices.
• Experience implementing machine learning models and workflows across multiple model classes or scientific domains.

Conditions

This is a short-term engagement.

Pay is $7,000 to $9,000 per month.

Not eligible for health and welfare benefits.

Pay and benefits reflect the company's good faith estimate at the time of posting and may change later.