---
title: 'Scientist I, Computational Protein Design at Generate Biomedicines'
canonical: 'https://feeny.ai/job/scientist-i-computational-protein-design-generate-biomedicines-somerville-6n26sf6x6wva'
type: 'job'
last_seen: '2026-10-30'
---

# Scientist I, Computational Protein Design at Generate Biomedicines

- **Company:** Generate Biomedicines
- **Location:** Somerville, MA
- **Compensation:** $140k–$196k
- **Posted:** 2026-10-21
- **Last confirmed live:** 2026-10-30
- **Apply:** https://generatebiomedicines.com/open-positions?gh_jid=4723323006

## Job description

The Role:

We are seeking an inventive Computational Protein Design Scientist to join our team working at the interface of computational protein design, machine learning, and experimental biology. In this role, you will use your computational expertise and in-depth biochemical understanding of proteins to drive computational protein design strategy for therapeutic programs while helping develop reusable design capabilities to unlock novel design challenges. The role interfaces between our machine learning and experimental platform teams, working closely to efficiently integrate AI-designed proteins and experimental data.

You will combine hands-on protein design with computational experimentation and close partnership across program, experimental, and computational teams. You will translate therapeutic hypotheses into design and data-generation plans, execute protein design campaigns, interpret results, and help guide decision-making in fast-paced cross-functional teams.

You will also feed back application learning to drive platform capability development by identifying recurring needs, successful approaches, and failure modes. This work will help shape new design methods, workflows, and scientific requirements that make program execution more efficient, reproducible, and scalable.

Here's how you will contribute:

- Drive therapeutic protein design. Leverage novel computational tools, biochemistry, and structural biology knowledge to translate therapeutic hypotheses and program needs into end-to-end protein design campaigns, data strategies, and technical milestones, highlighting and navigating key uncertainties.
- Connect application learning to capability development. Identify recurring capability gaps, successful approaches, and failure modes, and translate these insights into improved methods, workflows, and priorities.
- Connect design and experimental learning. Serve as an effective interface between computational model development and experimental validation, feeding biological learnings back to computational collaborators and vice versa. Use biochemical background to shape the most informative experiments involving complex assay readouts, signal and noise properties, and experiment design tradeoffs.
- Develop and apply agent-enabled computational workflows. Contribute directly to building workflows that connect scientific information, protein-design models, data, and tools, and apply them to program questions and design decisions. Evaluate their outputs and reliability in the context of the decisions they support.
- Translate results into program decisions. Develop and communicate clear, data-driven design recommendations that connect molecular observations to program context and next-step decisions, and document assumptions, results, and limitations so the work is understandable and reusable.

The Ideal Candidate will have:

- A PhD in protein engineering, biochemistry, bioengineering, molecular biology, computational biology, bioinformatics, or a related field.
- Demonstrated experience formulating protein design strategy in areas including de novo protein design, protein optimization, protein engineering, antibody engineering, or related molecular-design problems.
- Strong practical understanding of protein sequence, structure, and their relationship to molecular properties and biological function.
- Experience with experimental design and interpreting complex biological datasets to guide protein design decisions.
- Working proficiency in Python and the ability to develop reproducible analyses and computational workflows.
- Strong scientific judgment, creativity, and the ability to propose and act on decisions with incomplete information.
- The ability to communicate technical concepts, assumptions, risks, and tradeoffs clearly to cross-functional audiences.
- Experience with machine learning, statistical modeling, developing AI-agent workflows, workflow orchestration, or programmatic interfaces is valuable but can be developed in the role.

Who Will Love This Job:

You are inventive and entrepreneurial, with the initiative to pursue promising ideas and the discipline to test them rigorously. You bring a collaborative, low-ego approach to scientific problem solving, communicate with clarity and context, and adapt your decisions as new evidence develops.

Location:

This role is based in our Somerville, Massachusetts office with flexibility for hybrid work.

## #LI-HM1

## About Generate Biomedicines

We are a clinical-stage generative biology company pioneering the AI revolution in drug design and development. We are advancing a new approach to drug creation—one grounded in the ability to design proteins with defined biological intent. By integrating machine learning with large-scale experimentation, this approach aims to reduce the uncertainty, time, and cost associated with developing protein-based medicines.

Founded in 2018, we are advancing a growing pipeline of clinical and preclinical programs across multiple disease areas and protein modalities. By unifying computational design and clinical development within a single operating model, we translate this approach into clinical-stage programs and are leading a shift from traditional drug discovery toward systematic drug generation.

At Generate:Biomedicines, we collaborate across disciplines in new ways to invent and innovate. We bring diverse perspectives to a shared goal of delivering better medicines to patients in need, faster, guided by our values and leadership behaviors.

Generate:Biomedicines 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.

Recruitment & Staffing Agencies: Generate:Biomedicines does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Generate:Biomedicines or its employees is strictly prohibited unless contacted directly by the Company’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Generate:Biomedicines and the Company will not owe any referral or other fees with respect thereto.

Compensation: The base salary range provided reflects our current estimate of what we anticipate paying for this position. Your actual base salary will be based on several factors, including job-related skills, experience, internal equity, relevant education or training, and market dynamics. In addition, you will be eligible for an annual bonus, equity compensation, and a competitive benefits package.

Per Year Salary Range $140,000—$196,000 USD

## About Generate Biomedicines

## Company Overview
- **One-liner**: Generate Biomedicines is a clinical-stage generative biology company pioneering the use of machine learning to design and develop protein-based medicines on demand.
- **Entity Type**: Public (ticker: GBIO)
- **Headquarters**: Somerville, Massachusetts, USA (Boynton Yards and Andover locations)
- **Founded**: 2018
- **Founders**: Gevorg Grigoryan, Daria Hazuda, and others

## Core Business
- **Primary industry**: Biotechnology / Drug Discovery & Development
- **Target customers**: B2B (pharmaceutical partners) and patients (via clinical programs)
- **Mission statement**: "We don’t discover medicines—we design them," with a belief that speed is a moral obligation to patients.

## Products & Services
- **[Generate Platform™]**: An integrated computational and biohardware innovation stack that uses generative biology to design proteins with defined biological intent. It can generate up to a billion designed variants per cycle with cycle times as fast as ~8 days.
- **[GB-0895 (Anti-TSLP Antibody)]**: A next-generation anti-TSLP monoclonal antibody for severe asthma and COPD, currently in global Phase 3 trials. Designed for ultra-high affinity (106 fM binding, 20x improvement over tezepelumab) and an extended half-life (98 days, longest known among TSLP-targeting therapies), enabling twice-yearly subcutaneous dosing.
- **[GB-5267 (MUC-16 Armored CAR-T)]**: A cell therapy candidate for metastatic ovarian cancer, expected to enter Phase 1 in 1H26.
- **[GB-4362 (Free MMAE Toxin Neutralizer)]**: A first-in-class neutralizer designed for combination with MMAE-based antibody-drug conjugates (ADCs), with Phase 1 initiation in bladder cancer expected 1H26.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed; IPO in February 2026 raised net proceeds of approximately $370 million.
- **Key Metric**: $221.5 million cash balance at YE 2025, plus ~$370 million from IPO (early 2026).
- **Notable Investors/Partners**: Strategic collaborations with Amgen, Novartis, MD Anderson Cancer Center, and Roswell Park Comprehensive Cancer Center.
- **Growth Signals**: 5 clinical-stage programs enabled by the platform; initiated global Phase 3 studies for GB-0895; operating out of 140k+ square feet of lab and office space; has studied millions of proteins and generated 42,000 proteins built and tested.

## Competitive Advantages
- **Fully integrated computational-biohardware loop**: Machine learning drives generative design, which feeds directly into high-throughput experimentation (including proprietary CryoEM with four of the best microscopes in the world), and results continuously train the AI system — a "living feedback loop" that compounds over time.
- **Multimodal platform**: Can generate candidates across antibodies, CAR-T, and other protein modalities from a single core technology, enabling a pipeline that covers both immunology and oncology.
- **Record speed and scale**: Capable of generating up to a billion designed variants in ~8-day cycles, dramatically reducing the time and cost traditionally associated with drug discovery.
- **First-mover in next-gen anti-TSLP**: First known next-generation anti-TSLP antibody to enter the clinic (GB-0895) with a differentiated half-life profile that could enable twice-yearly dosing, a significant competitive edge in a large market.

## Strategic Focus
- **Clinical execution**: Advancing GB-0895 through global Phase 3 trials in severe asthma (with data in 2H27/1H28) and initiating late-stage development in COPD.
- **Pipeline expansion**: Moving GB-5267 (CAR-T) and GB-4362 (ADC neutralizer) into Phase 1 in 2026, expanding the platform's therapeutic scope.
- **Platform scaling**: Continuing to refine the generative biology engine to unlock new modalities and therapeutic areas, while deepening existing strategic collaborations with major pharma partners.
- **Organizational growth**: Building out the team across computational, wet-lab, clinical, and operational functions to support the growing pipeline.

## Why Work Here
- **Mission-driven**: The company is explicit that "speed is not just a competitive advantage—it’s a moral obligation." Employees are directly involved in designing drugs rather than discovering them, with a focus on getting treatments to patients faster.
- **Interdisciplinary culture**: The company emphasizes true integration across machine learning, biological engineering, and medicine. As stated on their site, "We are a close-knit group of cross-disciplinary experts... each conversant in one another’s fields, working together to create a new one."
- **Cutting-edge technology**: Access to unique computational and biohardware infrastructure, including "the four best CryoEM microscopes in the world" and a high-throughput experimental loop that powers AI training in real-time.
- **Values-driven leadership**: Explicit leadership behaviors include "value the knowledge we gain more than the knowledge we have," "bring creativity, tenacity, and ingenuity to every challenge," and "hold oneself and others to an obligation to dissent."
- **Hybrid/office policy**: Not explicitly stated, but the company operates large physical facilities in Somerville and Andover, MA, and offers free parking, monthly subway passes, or subsidized commuter rail passes, suggesting a significant on-site expectation.
- **Comprehensive benefits**: Competitive pay, employee stock option plan, health/vision/dental insurance, long- and short-term disability, life insurance, EAP, retirement savings, paid parental/adoption/caregiver leave, free weekly lunch, and stocked kitchen.
- **Growth trajectory**: As a newly public company with a cash-rich balance sheet and multiple catalysts over the next 12–24 months, the company offers significant career growth potential for those who want to be part of building a "transcendent company" that redefines an industry.

## Sources
1. [generatebiomedicines.com](https://generatebiomedicines.com/)
2. [generatebiomedicines.com/careers](https://generatebiomedicines.com/careers)
3. [generatebiomedicines.com/about-us](https://generatebiomedicines.com/about-us)
4. [investors.generatebiomedicines.com](https://investors.generatebiomedicines.com/)
5. [Non-Confidential Overview (April 2026)](https://investors.generatebiomedicines.com/wp-content/uploads/2026/04/Generate-Biomedicines-Non-Confidential-Overview_April-2026-1.pdf)

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