Data selection and quality evaluation for biological foundation models
Company websiteinceptive.com (Inceptive, opens in new tab)
Base salary $135K to $240K
Employer-published annual base salary, USD. Advertised base range in Berlin, NH +3 more
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationBerlin, NH +3 more
- WorkplaceWorkplace not stated
- Status at last checkSource accepting applications when checked
- Last checked (3 h ago) · observed since
All places named
- Berlin, NH
- Palo Alto, CA
- Germany
- Zurich, Switzerland
About this job
At Inceptive, you will help pioneer the next generation of AI-designed drugs, with the potential to positively impact billions of people, as part of a collaborative, antedisciplinary team.
We advance the state of the art in molecular design by training large-scale foundation models that enable cutting-edge generative approaches. Those models depend on rich, high-quality experimental data that captures biological function. Progress requires not only building better models, but also designing better experiments, understanding measurement systems, and generating datasets that faithfully represent underlying biology.
You will collaborate closely with biologists and machine learning researchers to design, analyze, and improve the experiments that power our models. You will help determine what data should be generated, how experiments should be structured, how measurement artifacts can be identified, and how biological insights can be translated into scalable data generation strategies.
Your Mission, should you choose to accept it
- Embody our vision of an antedisciplinary environment and embrace learning about areas outside of your traditional area of expertise
- Develop statistical and computational approaches to characterize assay quality, reproducibility, and sources of experimental variation
- Identify and investigate sources of bias and measurement artifacts in biological datasets
- Design and analyze large-scale biological experiments that generate training and evaluation data for machine learning models
- Partner with experimental scientists to improve assay design, controls, and data collection strategies
- Collaborate with machine learning researchers to understand how experimental design decisions impact model training and evaluation
- Analyze, visualize, and communicate findings to support decision-making across scientific and engineering teams
Qualifications
- PhD in computational biology, systems biology, genomics, bioengineering, biostatistics, biophysics, or a related quantitative discipline, or equivalent practical experience
- Demonstrated track record of analyzing complex biological datasets and translating computational insights into experimental validation or new data collection
- Strong foundation in experimental design, statistical analysis, and quantitative reasoning
- Deep understanding of sources of experimental variability, batch effects, and assay artifacts in biological data
- Capable programmer in Python and common scientific computing libraries
- Excellent written and verbal communication skills, including the ability to communicate effectively across computational and experimental disciplines
- Availability to work with team members across US and Europe, with meetings starting at 8am PT and ending at 7pm CET
- Readiness to travel several times a year for company retreats and business events
- We value the benefits of in-person collaboration and expect candidates to primarily work from our office locations
Preferred technical skills
- 3+ years of post-PhD experience in computational biology, biostatistics, or a related field
- Experience connecting experimental outcomes to machine learning model development and evaluation
Compensation
$135K – $240K + Bonus + Equity
What we offer
- A competitive compensation package
- 30 days paid vacation per year
- Comprehensive health insurance for US based Beginners
- 401K with company match for US based Beginners and Direktversicherung for German Beginners
- Quarterly company-wide retreats
- Monthly wellness benefit
- Budget for multiple visits per year to our offices in Berlin, Palo Alto or Switzerland
- Learning & Development budget to attend conferences, take courses, or otherwise invest in your professional growth
- A buddy to help you get settled
*Varies by country and does not apply to internships
At Inceptive, we are creating tools to develop increasingly powerful biological software for the rational design of novel, broadly accessible medicines and biotechnologies previously out of reach. Our team brings together vast expertise in molecular biology, machine learning, and software engineering, and we are all working towards becoming antedisciplinary, meaning we deepen the knowledge we have in our area of expertise while also expanding our knowledge of completely new fields.
We approach our goals with a Beginner's mind, humbly and with fresh eyes, and aim to become the pioneers of a new discipline rooted in biology as much as in deep learning, whose impact will be realized together with out-of-the-box thinkers in business and entrepreneurship, defying established categorizations. We are building a company culture centered around growth, learning, and discovery. We believe in humility and open-mindedness in how we approach each other, as well as problems we don't yet have solutions for.
It is the policy of Inceptive to ensure equal employment opportunity without discrimination or harassment on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, age, disability, marital status, citizenship, national origin, genetic information, or any other characteristic protected by law. Inceptive prohibits any such discrimination or harassment.
Inceptive is also committed to welcoming and providing accommodations to people with disabilities. Please let us know if you need any accommodations throughout your application process.
Source: Inceptive on Greenhouse · View original posting (opens in new tab)
This listingData selection and quality evaluation for biological foundation models$135K to $240K
Computational design of biological experiments for model development$135K to $240K
High-throughput data generation to advance ML design$135K to $240K
Open apply$105K to $240K
Foundation and generative models for biomolecules$200K to $275K
Chart as a table
| Role | Published base |
|---|---|
| Data selection and quality evaluation for biological foundation models (this listing) | $135K - $240K |
| Computational design of biological experiments for model development | $135K - $240K |
| High-throughput data generation to advance ML design | $135K - $240K |
| Open apply | $105K - $240K |
| Foundation and generative models for biomolecules | $200K - $275K |
Observed changes
- First observed on the employer's board
- Began meeting the published-salary criteria
- Observed since
- Employer-stated posting date
- 2026-07-17
Where this pay comes from
Location as the employer wrote it: Berlin, Germany or Palo Alto, CA or Zurich, Switzerland
$135K – $240K + Bonus + Equity
- Method
- Employer text, read with fixed rules and re-verified
- Checked
- Rule set
- us-base-v2
The pay passage appears in the employer's own job text. Fixed, deterministic rules located it, and the passage below was checked against the stored copy of the posting.
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.
