---
title: 'Member of the Technical Staff, Biological Data at Output Biosciences'
canonical: 'https://feeny.ai/job/member-of-the-technical-staff-biological-data-output-biosciences-new-york-6z41abthyzrk'
type: 'job'
last_seen: '2026-09-16'
---

# Member of the Technical Staff, Biological Data at Output Biosciences

- **Company:** Output Biosciences
- **Location:** New York, NY
- **Compensation:** $150k–$350k
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-07-27
- **Last confirmed live:** 2026-09-16
- **Apply:** https://jobs.ashbyhq.com/output/a98270b8-768c-4460-90d4-90cae895e669

## Job description

## The Role

Output has built a biological reasoning model that understands biology at the scale and complexity life actually operates. Our model independently learned the principles of molecular interactions, opening up drug treatments that were previously impossible. We're already generating therapies that traditional approaches cannot reach. The hardest problems in both AI and biology are being solved here, and there is room for you to own one. Output is currently in stealth, operated by a team of repeat founders and biotech veterans with multiple exits in AI x Bio, and backed by top-tier VCs including Y Combinator. You will own the data that our models learn from. This role requires a deep understanding of molecular biology - what a biological data source contains, what it implies, and what is missing. The quality and coverage of training data determines what our models can learn, and the biological insight behind how that data is constructed is the difference between a model that memorizes and one that reasons.

- You will construct training datasets that capture how proteins and molecules interact, drawing from diverse biological data sources and extending them with your understanding of molecular principles
- You will develop methods to expand training data beyond what exists in public databases, using biological and chemical reasoning to create new training signal where current data is sparse or absent
- You will design benchmarks grounded in real molecular phenomena, measuring whether our models have learned biologically meaningful capabilities rather than statistical shortcuts
- You will develop data strategies in collaboration with model researchers, determining what the model should learn from, what biological signal to prioritize, and how to sequence learning across modalities
- You will design approaches for integrating data across biological scales and modalities, building coherent training data from heterogeneous experimental and computational sources
- You will design rigorous splitting and evaluation strategies that prevent leakage and ensure model capabilities generalize to real biological problems
- You will stay current with biological data sources, experimental methods, and molecular databases, continuously identifying new sources of training signal

## About You

- You have a PhD in computational biology, biophysics, structural biology, chemistry, biochemistry, or a related biological field with 2+ years of post-doctoral or industry research experience, or equivalent depth through a combined biology and computational background
- You have deep understanding of molecular interactions, protein structure, and biological data at the molecular level, grounded in first principles rather than surface familiarity
- You have experience working with large-scale biological or molecular datasets, including sourcing, cleaning, integrating, and analyzing heterogeneous data
- You have strong programming skills in Python and are comfortable building computational pipelines for data processing at scale
- You understand what machine learning models require from training data: coverage, quality, balance, and evaluation rigor
- You approach data construction as a research problem, not a pipeline task: you think carefully about what data means, what signal it carries, and what is absent

Bonus Points

- You have experience with computational biology tools such as structure prediction, molecular docking, or virtual screening
- You have experience training or evaluating machine learning models, particularly on molecular or biological data
- You have publications in computational biology, bioinformatics, or molecular informatics
- You have a background in cheminformatics or molecular data analysis
- You have experience working with protein or molecular language models

## Our Values

❤️ Heart: We foster a culture of ownership. We are assembling a team of individuals who are passionate and take pride in their contributions. 🏆 Excellence: We have an unwavering commitment to excellence and continuously challenge ourselves to reach the highest standards. 🚀 Practicality: We value practicality and results-oriented thinking. We are committed to making a tangible impact on the lives of patients and the broader community. 📣 Honesty: We place a high value on honesty and directness. We firmly believe in addressing issues as they arise, in an open and transparent manner. 🎮 Fun: We believe that life is too short to not have fun. Our goal is to create a workplace that is fun, engaging, rewarding and fulfilling.

## What We Offer

- We encourage new and different ideas, creativity and contrarian thinking
- Healthy feedback focused environment to help you strive - leadership will have high expectations, regularly share constructive feedback, support you and help you grow, and welcome receiving feedback and ideas from you
- You own your day-to-day management. What we care about is that we all hit our milestones
- Competitive salary and equity in a growing, well-funded startup
- Excellent medical, dental, and vision coverage

## About Output Biosciences

## Company Overview
- **One-liner**: Output Biosciences is pioneering Biologically-Aware Generative AI to understand complex biological systems and generate breakthrough medicines.
- **Entity Type**: Private (Seed stage, Y Combinator S21 batch)
- **Headquarters**: New York, New York, United States
- **Founded**: 2021
- **Founders**: Mirella Mashiach (Co-Founder) and other repeat founders of AI-driven biotech startups

## Core Business
- **Primary industry/industries**: Biotechnology Research, Generative AI, Drug Discovery
- **Target customers**: B2B (pharmaceutical and biotech companies), Enterprise (research institutions)
- **Mission or purpose statement**: "Teaching Generative AI the Language of Biology" to advance humanity to a new level of health by building Large Biological Models that can generate breakthrough medicines.

## Products & Services
- **Large Biological Models**: A new generative AI architecture designed to handle the extremely long, nonlinear, fragmented, and high-dimensional data of biological systems. These models aim to transform the way diseases are diagnosed, treated, and prevented.
- **Biologically-Aware Generative AI Platform**: A proprietary platform that understands complex biological systems, enabling the generation of novel therapeutic candidates and insights.

## Market Standing
- **Valuation/Market Cap**: Not publicly available (private company)
- **Key Metric**: Total Funding – Seed round (2023) and Pre-Seed round (2021) from Y Combinator and other investors; exact amounts not disclosed.
- **Notable Investors/Partners**: Y Combinator (Summer 2021 batch)
- **Growth Signals**: Headcount grew 50% YoY (from 2 to 4 employees); monthly website traffic grew 56.9% month-over-month and 98.3% year-over-year; 9 active job postings as of mid-2025, indicating aggressive hiring.

## Core Business
- Primary industry/industries: Biotechnology Research, Generative AI, Drug Discovery
- Target customers: B2B (pharmaceutical companies, biotech firms, research institutions)
- Mission or purpose statement: Teaching Generative AI the Language of Biology to understand complex biological systems and generate breakthrough medicines.

## Products & Services
- **Large Biological Models (LBMs)**: A proprietary generative AI architecture that can process the extremely long, nonlinear, fragmented, and high-dimensional data of biological systems. These models are designed to generate breakthrough medicines and transform the way diseases are diagnosed, treated, and prevented. Type: AI/Software platform.

## Market Standing
- **Valuation/Market Cap**: Not publicly available
- **Key Metric**: Total Funding – Pre-Seed round (August 2021) and Seed round (January 2023) from Y Combinator and other investors; exact amounts not disclosed.
- **Notable Investors/Partners**: Y Combinator (Summer 2021 batch)
- **Growth Signals**: Headcount grew 50% YoY (from 2 to 4 employees); monthly website traffic grew 56.9% month-over-month and 98.3% year-over-year; 9 active job postings as of mid-2025, indicating a significant hiring push.

## Competitive Advantages
- **Novel AI Architecture**: Their generative AI is specifically designed for biological data, which is "extremely long, nonlinear, fragmented, and high dimensional" — a fundamental challenge that standard LLMs cannot handle.
- **Founding Team Expertise**: Repeat founders of AI-driven biotech startups, with backgrounds in computational systems biology, nonlinear dynamics, and medicine.
- **Y Combinator Backing**: Part of the prestigious Y Combinator Summer 2021 batch, providing strong validation and network effects.
- **First-Mover in Biologically-Aware AI**: They are pioneering a new category of AI models that are "biologically-aware," a significant differentiator from general-purpose AI models applied to biology.

## Strategic Focus
- **Current priorities**: Building and scaling their core team of researchers and engineers to develop Large Biological Models. They are actively hiring across machine learning, computational biology, and interpretability roles.
- **Direction for growth**: Expanding from research to generating breakthrough medicines, with a focus on pretraining, molecular generation, and model interpretability.

## Why Work Here
- **Culture highlights**: A mission-driven environment focused on making a tangible impact on human health. The company emphasizes "impatience to see how your work improves people's lives."
- **Remote/hybrid/office policy**: Hybrid model with a strong New York HQ presence. Some roles are listed as "New York HQ" with a preference for in-person collaboration, while others (e.g., Machine Learning Engineer, Senior Computational Biologist) are available as remote positions.
- **Notable perks or engineering culture**: A small, tight-knit team (currently 4 employees) with a high degree of ownership and impact. The company is at the forefront of generative AI and biology, offering the chance to work on fundamental research problems. They are actively hiring for 9 roles, including research interns and senior computational biologists, indicating a strong commitment to building a world-class R&D team.

## Strategic Focus
- **Current priorities**: Expanding the core team across machine learning, computational biology, and interpretability. They are focused on pretraining large biological models and developing methods to understand and generate biological sequences.
- **Direction for growth**: Moving from foundational research to generating breakthrough medicines, with a clear pipeline toward therapeutic applications.

## Why Work Here
- **Culture highlights**: Mission-driven, high-impact environment where "impatience to see how your work improves people’s lives" is a core value. The team is small (4 employees) and collaborative, offering significant ownership and visibility.
- **Remote/hybrid/office policy**: Hybrid model with a strong New York HQ presence. Some roles (e.g., Machine Learning Engineer, Senior Computational Biologist) are listed as remote, while others are NYC-based. The company has two offices in New York.
- **Notable perks or engineering culture**: Opportunity to work at the cutting edge of generative AI and biology. The company is expanding its core team and has 9 active job postings, including research intern positions, making it accessible to new graduates as well as experienced professionals. The tech stack includes Python, TensorFlow, and PyTorch.

## Sources
1. [outputbio.com](https://outputbio.com/)
2. [ycombinator.com](https://www.ycombinator.com/companies/output)
3. [linkedin.com](https://www.linkedin.com/company/output-biosciences)
4. [jobs.ashbyhq.com](https://jobs.ashbyhq.com/output)

## Other roles at Output Biosciences

- [Member of the Technical Staff, Pretraining](https://feeny.ai/job/member-of-the-technical-staff-pretraining-output-biosciences-new-york-8m06djybaawf) — New York, NY
- [Member of the Technical Staff, Generative](https://feeny.ai/job/member-of-the-technical-staff-generative-output-biosciences-new-york-d7h39gzbcpqj) — New York, NY
- [Member of the Technical Staff, Cheminformatics](https://feeny.ai/job/member-of-the-technical-staff-cheminformatics-output-biosciences-new-york-d0azrngcqn26) — New York, NY
- [Member of the Technical Staff, Interpretability](https://feeny.ai/job/member-of-the-technical-staff-interpretability-output-biosciences-new-york-vnnp41pj7x8r) — New York, NY
- [Software Engineer, Agents](https://feeny.ai/job/software-engineer-agents-output-biosciences-new-york-bjkfjnfqzp3t) — New York, NY
- [AI Technical Recruiter](https://feeny.ai/job/ai-technical-recruiter-output-biosciences-remote-x12g46g758gq)
- [Head of Discovery](https://feeny.ai/job/head-of-discovery-output-biosciences-new-york-6t1706k1y2nz) — New York, NY
- [Head of Biology](https://feeny.ai/job/head-of-biology-output-biosciences-new-york-tjktcbm9rvtd) — New York, NY