ProFound Therapeutics: AI/ML Engineering - SAGE Platform Co-Op

This position is open exclusively to current Northeastern University Co-Op students.

Location: Watertown, MA
Work Period: January 2027 to June 2027. This is a full - time, 40 hours per week position with hybrid schedule.

About ProFound Therapeutics

ProFound™ Therapeutics is a biotechnology company discovering novel proteins across the expanded human proteome to unlock first-in-class medicines and transformative drug targets. The company’s proprietary ProFoundry™ Platform integrates state-of-the-art protein detection, validation, and computational technologies to systematically identify and characterize previously inaccessible proteins and validate their therapeutic potential. This approach has generated a rapidly expanding portfolio of novel targets and drug discovery programs advancing toward the clinic, enabled by strategic collaborations with leading pharmaceutical partners. Together, these efforts support the development of breakthrough treatments across a broad range of disease areas.

The company is now poised to define the disease-relevant function of these proteins at scale using advanced proteomics technologies, high throughput experimental biology, and causal agentic AI, enabling rapid identification and characterization of the most promising protein drugs and drug targets.

Founded by Flagship Pioneering, ProFound works with pharmaceutical partners including Novartis, Pfizer and GSK, and with the Gates Foundation, which has committed up to $35 million to a ProFoundprogram focused on preeclampsia.

About Flagship Pioneering

ProFound Therapeutics was founded by Flagship Pioneering's venture creation engine that invents and builds platform companies, each with the potential for multiple products that transform human health or sustainability. Since its launch in 2000, Flagship has originated and fostered more than 100 scientific ventures, resulting in more than $90 billion in aggregate value. Many of the company’s Flagship has founded have addressed humanity’s most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture. Flagship has been recognized twice on FORTUNE’s “Change the World” list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies and has been twice named to Fast Company’s annual list of the World’s Most Innovative Companies. Learn more about Flagship at .

Flagship Pioneering Co-Op Program

Welcome to Flagship Pioneering Co-Op Program for the cohort dreaming big and taking courageous leaps. You'll join fellow peers across our ecosystem of companies and learning firsthand how we build first-in-category companies. You’ll have access to enrichment sessions , a dedicated professional development track , and a mentor that help guide you toward your next step. By the end, you will carry on a meaningful project outcome , a genuine network , and a front-row view of how Flagship pioneer new ventures that change the world.

Position Summary

ProFound’s AI/ML team builds SAGE, an internal multi-agent LLM platform that helps our scientists reason over knowledge graphs, biological databases and the scientific literature. SAGE is a central part of how ProFound applies agentic AI to understand novel proteins and accelerate drug discovery.

As an AI/ML Engineering Co-Op, you will help extend what SAGE can do and make sure it performs reliably. You will own real features from design through deployment, working closely with our ML engineers and with the scientists who use SAGE every day. The Co-Op is designed to complement your academic training with hands-on experience building and operating a production AI system in an industry drug discovery setting.

Scope

• Agent tools and integrations, including external data sources, MCP servers and user-uploaded documents
• User experience and collaboration features in the SAGE chat interface
• LLM evaluation and benchmarking (answer quality, accuracy and hallucination rate)
• Monitoring of usage, performance and cost, and quality checks in CI/CD

Key Responsibilities

Responsibilities include, but are not limited to, the following.

• Tools and capabilities
  • Design, build and ship new SAGE tools that connect the agent to external data sources, APIs and MCP servers.
  • Extend SAGE’s ability to ingest and reason over documents that users upload, including parsing, chunking and retrieval.
  • Contribute to agent orchestration and retrieval-augmented generation (RAG) components that work across knowledge graphs, biological databases and the scientific literature.
• User experience
  • Build features that make the SAGE chat interface easier to use and collaborate in (e.g., sharing conversations, displaying sources and citations).
  • Gather feedback directly from scientists and turn it into practical, prioritized improvements.

• Evaluation and quality
  • Develop evaluation and benchmarking pipelines that measure SAGE’s answer quality, accuracy and hallucination rate.
  • Help build and curate benchmark datasets with input from scientists, using automated (e.g., LLM-as-judge) and human-review approaches.
  • Help integrate automated quality checks and regression tests into our CI/CD pipeline.
• Monitoring and engineering practice
  • Build monitoring for SAGE usage, performance, reliability and LLM cost.
  • Write clean, tested and documented code, and take part in code reviews.
  • Present progress and results to the AI/ML team and scientific stakeholders, including a final co-op presentation.

What Success Looks Like by the End of the Co-Op

• At least one new SAGE capability designed, built and deployed to production, and in use by scientists.
• An evaluation and benchmarking pipeline running regularly, giving the team a clear baseline for answer quality and hallucination rate.
• Better visibility into SAGE usage, performance and cost.
• Well-documented work that the team can maintain and build on after the co-op ends.

Qualifications

Required

• Currently pursuing a B.S. or M.S. in Computer Science, Artificial Intelligence, Data Science, or a related field, and available for a full-time, 4–6 month co-op term.
• Strong Python skills.
• Hands-on experience building with LLMs (e.g., LLM APIs, RAG, agents, or MCP) through coursework, projects, or prior internships
• Familiarity with Git and software engineering best practices, such as testing, code review and documentation.
• Curious and self-driven, with the ability to communicate clearly with technical and non-technical colleagues.

Preferred

• Experience with web or backend development (e.g., FastAPI, React or TypeScript).
• Experience with LLM evaluation frameworks or observability and tracing tools.
• Exposure to knowledge graphs, vector databases, or scientific and biological data sources.
• Familiarity with cloud environments (e.g., AWS), containers (e.g., Docker) and CI/CD tooling (e.g., GitHub Actions).
• Prior internship or co-op experience in software or ML engineering.
• Interest in biology or drug discovery; no biology background required.

Why Join Us?

You’ll work on a production AI platform used by real scientists. You’ll own projects end to end, with mentorship from experienced ML engineers, and contribute to the discovery of new medicines.

What We Offer

• Build alongside founders. You’ll work inside the same hypothesis-driven process Flagship uses to conceive and launch first-in-category companies.
• This can be the start of a longer story. Strong co-ops are considered for future opportunities across Flagship and its portfolio companies, not just for this one role.
• Work alongside people who left the safe path . Your colleagues are scientists, engineers, and operators who chose to build something new rather than join something already established.
• Take on real ownership. You're contributing to ventures that are still being defined. Your work can shape real decisions, not just support them.
• Be paid like the contributor you are. Compensation reflects the real work you take on.

Flagship Pioneering is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

The pay range for this role is $25 - $35 per hour. This role is a short-term engagement that is not eligible for health and welfare benefits. Retirement benefits may be available after completing a set number of hours. Compensation and benefits information is based on ProFound's good faith estimate as of the date of publication and may be modified in the future.

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