Six Figure Work

Member of Technical Staff - Machine Learning

Inductive Bio

Company websiteinductive.bio (Inductive Bio, opens in new tab)

Base salary $180K  to $250K

Employer-published annual base salary, USD. Advertised base range in New York City, NY +2 more

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  • LocationNew York City, NY +2 more
  • WorkplaceHybrid
  • Status at last checkSource accepting applications when checked
  • Last checked (2 h ago) · observed since
All places named
  • New York City, NY
  • San Francisco, CA
  • Boston, MA

About this job

Drug discovery is a hierarchical reinforcement-learning problem with a vast action space and years-long horizon. Scientists design and synthesize molecules that they predict will be potent, safe, and readily absorbed into the body, but this typically requires years of iteration in the lab and millions of dollars to develop a molecule that is ready for testing in human.

At Inductive, we're building the AI and machine learning tools to radically accelerate this process. Our state-of-the-art predictive models and medicinal chemistry agents identify the right compounds to make at the right time, while our AI-integrated lab shortens the time to synthesize and test them. Our ADMET/PK models have placed first in the world’s largest AI drug discovery competition for ADMET benchmarks three consecutive times, and our technology is already being applied across dozens of biopharma partnerships.

Backed by leading technology and biotechnology investors including a16z, Lux, S32, and Obvious, our team brings together world-class expertise in machine learning and drug discovery.

We are seeking a Member of Technical Staff, Machine Learning to join our talented, ambitious, and kind team. You’ll innovate on ML methods, work closely with leading drug discovery scientists, and see your work applied directly to real drug programs. You’ll have significant ownership, impact, and opportunity to grow with the company.

What you’ll do:

  • Develop machine learning models to predict molecular properties from chemical structures

  • Develop novel algorithms for generate and prioritize molecules for synthesis

  • Build agents that can analyze complex information from drug programs and apply that information strategically toward molecular optimization

  • Get your hands dirty by diving deep into our unique, proprietary dataset to iterate on modeling ideas and improve model performance

  • Collaborate closely with chemists and software engineers to integrate models into our software platform, which is used by drug discovery scientists across the industry

  • Build and optimize scalable infrastructure for model training, deployment, and monitoring

  • Engage directly with our scientific users, incorporating their feedback into the product

  • Contribute meaningfully to product strategy and company direction

Who you are:

  • You have 4+ years of experience as a Machine Learning Scientist, Machine Learning Engineer, or similar role

  • You have a strong scientific background, ideally with a PhD in chemistry, biology, physics, or a related field

  • You have expertise in machine learning fundamentals, deep learning architectures, and evaluation approaches

  • You are proficient in standard Python-based ML frameworks (e.g. PyTorch, JAX, TensorFlow)

  • You are comfortable writing high-quality, reusable code and productionizing models for serving in the cloud

  • You are excited to dive deep into the science and practice of drug discovery

  • You have exceptional written and oral communication skills

  • Preferred experience:

    • You have graduate-level knowledge of cell / molecular biology or biochemistry, and experience collaborating with wet lab scientists

    • Experience with omics modeling (transcriptomics, proteomics, metabolomics, etc)

    • Experience with high-content screening and signal processing from microscopy data

Working at Inductive

At Inductive Bio, we know that the people on the team are what make us great. 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. We are a passionate, kind, and mature team. 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.

Source: Inductive Bio on Ashby · View original posting (opens in new tab)

Pay in context

This role's base floor ($180,000) is above 61% of the 4,592 Data & ML roles nationwide listed on this site; 135 others list the same floor. Their median floor is $165,000; the middle half runs from $135,000 to $198,180.

Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 8, 2026.

This range next to 2 other live Inductive Bio roles with the nearest advertised base floor
Chart as a table
This range next to 2 other live Inductive Bio roles with the nearest advertised base floor
RolePublished base
Member of Technical Staff - Machine Learning (this listing)$180K - $250K
Member of Technical Staff - Software Engineering$180K - $240K
Synthetic Chemist$210K - $250K

Same $100K to $400K scale as every card. All Inductive Bio roles · How to read the bar

Observed changes

  1. First observed on the employer's board
  2. Began meeting the published-salary criteria
Observed since
Employer-stated posting date
2026-09-11
Where this pay comes from

Location as the employer wrote it: New York City, San Francisco, or Boston

USD 180,000 – 250,000 · 1 YEAR · Salary

Method
Structured pay field published by the employer
Checked
Rule set
us-base-v2

The employer's job board publishes this pay as a dedicated data field. We read the field directly; no interpretation was needed.

What we verified

  • The pay figures come from the employer's own listing, quoted exactly above.
  • The pay is an annual base salary in US dollars with a minimum of at least $100,000.
  • The role was publicly listed on the employer's job board when last checked.

We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.

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