Computational Chemist (Machine Learning) I / II at Aralez Bio
Berkeley, CA
$165,000–$180,000from the description
Jul 22, 2026
Berkeley, CA
Jul 23, 2026
What this job asks for AI summary
A machine learning role embedded within an R&D team at a biotech, focused on building and deploying predictive models for chemical property prediction and de novo design of small molecules and peptides. The work spans constructing data pipelines from experimental screening data, applying chemoinformatics tools, and collaborating directly with laboratory scientists to translate research questions into actionable ML outputs. Best suited to someone with a graduate degree in a computational chemistry-adjacent field and hands-on experience shipping ML models in a scientific context.
Mid level · 2+ years · San Francisco-Oakland-Berkeley, CA · Master's required · Full-time
Posted 2 times — it's one opening, so apply once.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Roughly 310 people in the San Francisco-Oakland-Berkeley, CA area plausibly meet what this posting asks for (data scientists). range 80–400
Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.
Rare in this occupation — lead with these, and say what you built with them.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $173,851 (middle half $133,298–$217,653). This posting is about at that midpoint.
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (6)
The JD requires a Ph.D. or Master's degree in Computational Chemistry, Chemoinformatics, or a related field — Master's is set as the minimum hard-required degree.
Post-graduate experience is stated as '2-4 years'; the overall years minimum is set to 2 (the lower bound). The scope (owning models end-to-end, influencing ML infrastructure direction) is consistent with a Mid-level role given the relatively short experience window and startup context.
RDKit is listed with 'e.g.' as an example chemoinformatics toolkit, but it appears under the requirements block with firm language ('High proficiency with'); it is treated as a hard gate on the chemoinformatics toolkit capability, with RDKit as the named representative.
REINVENT and molecular dynamics simulations are explicitly flagged as 'a plus' in the posting and are therefore preferred.
Data visualization is listed in the requirements section but no specific tool is named (e.g., Matplotlib, Seaborn, Plotly); it is captured as a generic required skill since no concrete tool name is given.
The role is explicitly on-site in Berkeley, CA — remote is false.
Read the full posting
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