---
title: 'Member of Technical Staff - Computational Chemistry at Inductive Bio'
canonical: 'https://feeny.ai/job/member-of-technical-staff-computational-chemistry-inductive-bio-new-york-f0zh727srvv3'
type: 'job'
last_seen: '2026-09-09'
---

# Member of Technical Staff - Computational Chemistry at Inductive Bio

- **Company:** Inductive Bio
- **Location:** New York, NY / San Francisco, CA / Boston, MA
- **Compensation:** $180k–$230k
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-08-05
- **Last confirmed live:** 2026-09-09
- **Apply:** https://jobs.ashbyhq.com/inductive-bio/b0e17d5e-b487-4856-8a47-311600d33280

## Job description

Inductive Bio is an AI drug discovery partner. We help small molecule teams make better decisions, faster, across the full DMTA cycle. Our platform includes best-in-class ADMET models, human dose projection tools, an agentic AI drug discovery assistant, and high-throughput synthesis and testing services. Together, these power dozens of small molecule and beyond-rule-of-five programs for biotech and pharma partners.

Inductive’s Beacon-1 placed 1st in the three most recent consecutive OpenADMET blind challenges. We've raised $30M from top VCs, and were selected for a $21M ARPA-H CATALYST contract in collaboration with Amgen.

The Role:

We're looking for a seasoned computational chemist to join our team as a Member of Technical Staff, Computational Chemistry.

Each partner program is led by an Inductive pair: a computational chemist and a medicinal chemist. You'll own the modeling and co-own scientific delivery and impact, applying your expertise to real molecular optimization problems with a human dose-centric framework. You'll work across a wide range of small molecule modalities, therapeutic areas, and modeling challenges.

You'll also shape the development of Inductive's platform, from our predictive models and dose projection tools to Indy, informed by your own experience and what you see working (and not working) on real partner programs. We need someone whose instincts about what matters in small molecule optimization come from years of doing it, and who wants to put those instincts into the products we build.

This is a remote-friendly role, but we give bonus points to candidates located in Boston, New York, or San Francisco where we have physical offices. While we are flexible on the time zone for primary working hours, this role requires availability for external meetings that frequently occur during Eastern Time business hours.

What You'll Do:

Your time divides between partner-facing science and methods/product development. The split is flexible based on your interests and company needs; partner-facing science could be anywhere from 30% to 90% of your time.

Partner-facing science

- Co-own, together with an Inductive medicinal chemist, the scientific relationship with partner project teams. Our programs span reversible and covalent small molecules, macrocycles, molecular glues, and heterobifunctionals; you'll go deep where you have experience and stretch into the rest.
- Drive modeling strategy: which assays are most critical to model, how to model them, and how to use these predictions to make decisions that move the program forward.
- Bring order to messy program data. Rationalize SAR, identify what the data is and isn't telling you, and flag inconsistencies before they become bad decisions.
- Guide med chem strategy: what to make, what to test, how to triage compounds for advancement, and where to focus synthetic resources. Identify liabilities early and help partners build de-risking plans.
- Model in vivo outcomes end to end, from PK/PD/efficacy relationships to projected human dose, helping teams evaluate compounds through a dose-centric lens and reason about property tradeoffs in the context of therapeutic window.
- Represent Inductive's scientific capabilities in partner meetings and publications.

Methods and Product Development

- Prototype scientific analyses and modeling experiments in code. We use coding agents heavily within the Computational Chemistry team, so you can move from hypothesis to result quickly.
- Build reusable analyses, tools, and workflows for internal use, for partner delivery, and for Indy. If you find yourself doing something twice, automate it.
- Evaluate new computational methods on benchmark datasets and make pragmatic calls about what's worth adopting.
- Dig into model performance issues. When predictions miss, understand why and work with the ML team to turn those findings into model improvements.
- Stay current with the scientific literature and look for emerging techniques worth testing on real data.
- Set scientific direction for the platform. You won't just provide feedback on what others build; you'll define what needs to exist and why, grounded in your past experience and what you see on partner programs.
- Sit in product design meetings and own the user perspective. You use our tools every day; that makes you the most credible voice in the room for what's working and what isn't.
- Write feature requirements, prioritize the roadmap alongside product and engineering, and hold the bar on whether what ships actually solves the problem.
- Help grow the Computational Chemistry team as Inductive scales.

Who You Are:

- A pragmatic drug discovery scientist with 5+ years on project teams across multiple stages of discovery, from hit identification through lead optimization. You've developed strong opinions about what works and what doesn't, and partners trust your judgment at the technical, scientific, and strategic level.
- Broad technical range across cheminformatics, structure/physics-based modeling (docking/QM/FEP), ML, and DMPK. Deep scientific training in a relevant field is expected; the specific degree matters less than what you've done with it.
- Comfortable writing Python and picking up new tools. We use coding agents daily and prototype fast; strong coders with experience with AI coding agents will thrive here.
- Clear communicator who can lead cross-functional discussions and turn complex analyses into visuals that land with both technical and non-technical audiences.
- Bonus points if you've seen a program through to DC nomination or IND-enabling studies, or bring hands-on medicinal chemistry experience.

Working at Inductive:

We offer competitive salary and equity-based compensation; comprehensive healthcare benefits (including dental and vision); and the opportunity to grow along with a rapidly scaling company. Working at a fast-growing startup is not always a 9–5 job, but we believe that our employees should have full lives beyond their career.

## About Inductive Bio

## Company Overview
- **One-liner**: Inductive Bio provides an AI-powered virtual lab platform that enables chemists to run millions of in silico experiments to accelerate small molecule drug discovery.
- **Entity Type**: Private (Series A)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2022
- **Founders**: Josh Haimson (CEO) and Ben Birnbaum, Ph.D. (President and CTO)

## Core Business
- **Primary industry/industries**: Biotechnology Research, AI-driven Drug Discovery, Small Molecule Therapeutics
- **Target customers**: B2B, Enterprise biopharma companies, CROs (Contract Research Organizations)
- **Mission or purpose statement**: To accelerate small molecule drug discovery by pairing scientists with a virtual lab that can run millions of in silico experiments, surfacing the strongest hypotheses to test in the wet lab.

## Products & Services
- **[Indy, AI Chemistry Assistant]**: An AI tool that automates time-consuming chemistry operations and helps design and interpret experiments, acting like an entire chemistry team.
- **[Beacon-1, ADMET Models]**: A class of AI models trained on a pre-competitive data consortium for predicting Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) of molecules. It is fine-tuned to a client's chemical space and is benchmarked as state-of-the-art, winning 1st place in multiple blind competitions (e.g., OpenADMET 2025, 2026).
- **[Compass, Virtual Lab Software]**: A platform that gives direct access to run virtual experiments, review predictions, and decide which compounds to synthesize in real time.
- **[Partnered Services]**: Inductive can operate its virtual lab alongside a partner's team, delivering curated compound ideas. They also partner with select CROs to synthesize and test top compounds, creating an end-to-end, AI-informed feedback loop.

## Market Standing
- **Valuation/Market Cap**: Not publicly available
- **Key Metric**: Total Funding of $29.3M.
- **Notable Investors/Partners**: a16z Bio Health, Lux Capital, Obvious Ventures (Lead in Series A), Character Capital, Malay. Partners include Amgen (on a $21M ARPA-H initiative). The company also participates in a pre-competitive ADMET data consortium.
- **Growth Signals**: The company has 31 employees with a 120% yearly growth rate. They have delivered multiple development candidates (DCs) and have "dozens of partners." They are leading a $21M ARPA-H initiative with Amgen to develop AI drug toxicity models. Their Beacon-1 models have consecutively won 1st place in major blind ADMET competitions (Polaris, OpenADMET 2025, OpenADMET 2026), demonstrating superior technology. The company is SOC 2 compliant.

## Competitive Advantages
- **State-of-the-Art AI Models**: Their AI models are benchmarked as world-leading, having won 1st place in several large, blind ADMET prediction competitions against major pharma and AI drug discovery groups.
- **Human-Guided Virtual Lab**: The platform is designed to amplify, not replace, human chemists, combining the scale of AI with the expertise of veteran scientists.
- **Pre-competitive Data Consortium**: Access to large, diverse, and proprietary datasets from an industry consortium gives their models a training advantage over competitors.
- **End-to-End Acceleration**: Offers a complete loop from in silico design to virtual testing and then to synthesis with a CRO partner, which de-risks and speeds up the drug discovery process.
- **IP and Confidentiality**: Clients retain full IP ownership, and all data is kept completely confidential.

## Strategic Focus
- **Scaling the virtual lab**: Expanding the use of Beacon-1 and Compass across more biopharma partners.
- **Leading in Safety AI**: A key focus is on developing next-generation AI models for predicting drug toxicity in humans, as evidenced by the ARPA-H project.
- **Expanding the Data Moat**: Continuously growing the pre-competitive data consortium to improve model accuracy.
- **Delivering Development Candidates**: Proving the value of the platform by guiding multiple programs to achieve successful development candidates.

## Why Work Here
- **High-Caliber Team**: Work at the intersection of AI and life sciences with a team that includes experts from Google, Flatiron Health, Relay Therapeutics, and MIT. The leadership has deep experience in building innovative AI products and bringing drugs into the clinic.
- **Rapid Growth**: A fast-growing startup (120% YoY headcount growth) backed by top-tier investors (a16z, Lux, Obvious). This signals strong momentum and potential for career growth.
- **Impactful Mission**: Directly involved in accelerating the creation of new medicines, with tangible outputs like "DCs delivered."
- **Culture of Innovation**: The company is building a "virtual lab" that changes how chemistry teams work, using state-of-the-art AI and large datasets.
- **Location**: Based in San Francisco, a major hub for both tech and biotech.
- **Hiring for Growth**: The careers page indicates active hiring across key roles in the rapidly growing startup, suggesting opportunities for new joiners to make a significant impact [inductive.bio](https://www.inductive.bio/careers).

## Sources
1. [inductive.bio](https://www.inductive.bio/)
2. [inductive.bio](https://www.inductive.bio/careers)
3. [inductive.bio](https://www.inductive.bio/about)
4. [linkedin.com](https://www.linkedin.com/company/inductive-bio)
5. [cbinsights.com](https://www.cbinsights.com/company/inductive-bio)

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