---
title: 'AI Scientist at Nabla Bio'
canonical: 'https://feeny.ai/job/ai-scientist-nabla-bio-boston-841p9j67tmnh'
type: 'job'
last_seen: '2026-09-16'
---

# AI Scientist at Nabla Bio

- **Company:** Nabla Bio
- **Location:** Boston, MA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2025-08-25
- **Last confirmed live:** 2026-09-16
- **Apply:** https://jobs.gem.com/nabla-bio/am9icG9zdDps9ugWBZmvzPG0d4jtjs5M

## Job description

## The Role

We’re hiring an exceptional AI Scientist to lead development of our core biomolecular modeling technologies. You’ll be responsible for building and improving the foundation models that power Nabla’s therapeutic design capabilities — from architecture design and training to experimental validation. This is a rare opportunity to do AI research with real-world, large-scale experimental feedback: your models will be tested not just with loss curves and benchmarks, but in wet-lab assays measuring therapeutic function, safety, and precision. Our platform enables you to test dozens of modeling hypotheses in parallel, with experimental results across a million drug designs returned in just a few weeks. See our papers for examples of our work [[1](https://www.biorxiv.org/content/10.1101/2025.01.21.633066v1.full.pdf)][[2](https://www.biorxiv.org/content/10.1101/2025.05.28.656709v1.full.pdf)], and their coverage in [Science Magazine](https://www.science.org/content/article/ai-conjures-potential-new-antibody-drugs-matter-months) and [Endpoints News](https://endpoints.news/nabla-bio-moves-closer-to-ai-created-antibodies/).

This is an in-person role in Cambridge, MA. You will:

- Design, implement, and evaluate new training data, model architectures, training schemes, and loss functions for biomolecular generation and prediction
- Drive major improvements in generative and predictive performance based on experimental feedback
- Collaborate with AI engineers to productionize models for use in internal and pharma partner design workflows
- Stay on top of the state of the art in ML, protein modeling, and sequence design—and push it forward

## Qualifications

- 5+ years of experience developing deep learning models; prior experience in generative modeling, protein/biomolecular ML, or large-scale sequence modeling is a plus
- Strong engineering fluency in Python and PyTorch
- Experience with distributed training and scaling large models in HPC/cloud environments
- Track record of creativity, rigor, and technical leadership in ML research
- Comfort working closely with experimentalists to connect model behavior to real biological outcomes

## What We Offer

- The ability to test and validate ML hypotheses using one of the most powerful experimental platforms in biotech
- A chance to shape foundational modeling capabilities for programmable drug design
- Close collaboration with experts in wet-lab biology, bioinformatics, and software engineering
- A focused, technically ambitious team solving hard problems end-to-end
- Highly competitive salary, equity, and benefits package

## About Nabla Bio

## Company Overview
- **One-liner**: Nabla Bio uses AI and large-scale wet-lab experimentation to design antibodies against previously undruggable disease targets.
- **Entity Type**: Private (Seed-stage; $37M total funding)
- **Headquarters**: Cambridge, Massachusetts, USA
- **Founded**: 2020 (Y Combinator Summer 2020)
- **Founders**: Surge Biswas and Frances Anastassacos

## Core Business
- **Industry**: AI-powered drug discovery / Biotechnology (Antibody therapeutics)
- **Target Customers**: B2B – large pharmaceutical companies (AstraZeneca, Bristol Myers Squibb, Takeda)
- **Mission**: "Make drug development a true design discipline — reducing trial-and-error so better medicines can reach patients faster and with greater confidence."

## Products & Services
- **Generative Drug Design Platform**: Combines de novo AI antibody design with high-throughput, human-relevant wet-lab testing (binding, developability, cellular function, and in-vivo performance). The integrated dry/wet-lab system is built and owned in-house to enable an iterative design loop.

## Market Standing
- **Valuation/Market Cap**: Not publicly available
- **Key Metric**: $37M in total seed funding (backed by Radical Ventures, Khosla Ventures, and Zetta Venture Partners)
- **Notable Investors/Partners**: Radical Ventures, Khosla Ventures, Zetta Venture Partners, Y Combinator. Partners include AstraZeneca, Bristol Myers Squibb, and Takeda.
- **Growth Signals**: Revenue-generating since early stage; secured high-profile pharma partnerships (Takeda deal announced October 2025); continuing to hire top ML and synthetic biology talent.

## Competitive Advantages
- **Integrated dry/wet-lab engine**: Owns and controls the data, AI models, and experimental validation in one loop, rather than just providing software.
- **Focus on undruggable targets**: Aims to double the number of disease-relevant drug targets accessible to the industry.
- **Patient-relevant testing**: Wet-lab assays measure properties that matter in vivo, not just computational predictions.

## Strategic Focus
- Scaling the platform to design drugs with pre-specified properties (binding, safety, manufacturability).
- Deepening partnerships with top pharma companies to move designed molecules toward clinical development.
- Expanding the frontier of measurable disease targets.

## Why Work Here
- **Culture**: "Fully in-person and based in Cambridge, MA." The team values deep platform investment, high scientific standards, side-by-side collaboration, and learning quickly from results.
- **Work environment**: On-site only (Riverside Technology Center, Cambridge). The company emphasizes focus, urgency, and a "problems rather than prestige" mentality.
- **Team size**: ~22 employees (as of latest data), tight-knit mix of wet-lab and dry-lab scientists.
- **Open roles**: AI Platform Engineer, AI Scientist, and Applied AI/Bio Scientist – all based in Boston, MA.

## Sources
1. [nabla.bio](https://www.nabla.bio/)
2. [nabla.bio/careers](https://www.nabla.bio/careers)
3. [jobs.gem.com/nabla-bio](https://jobs.gem.com/nabla-bio)
4. [builtin.com/company/nabla-bio](https://builtin.com/company/nabla-bio)
5. [ycombinator.com/companies/nabla-bio](https://www.ycombinator.com/companies/nabla-bio)

## Other roles at Nabla Bio

- [AI Platform Engineer](https://feeny.ai/job/ai-platform-engineer-nabla-bio-boston-x7wjbrnnvzyz) — Boston, MA
- [Applied AI/Bio Scientist](https://feeny.ai/job/applied-ai-bio-scientist-nabla-bio-boston-fvzjj9kynby1) — Boston, MA
- [AI Scientist](https://feeny.ai/job/ai-scientist-mistral-paris-4gq664wdzm66) — Paris, France
- [AI Scientist](https://feeny.ai/job/ai-scientist-mistral-zurich-xt9n73m1vy41) — Zurich, Switzerland
- [AI Scientist](https://feeny.ai/job/ai-scientist-mistral-palo-alto-qp3962ww5jmv) — Palo Alto, CA
- [AI Scientist](https://feeny.ai/job/ai-scientist-mistral-warsaw-0w6gn8n7cxa9) — Warsaw, Poland
- [AI Scientist](https://feeny.ai/job/ai-scientist-poetiq-los-altos-ftv7qrhbzwcr) — Los Altos, CA