
Senior ML Research Engineer
Hover or tap a row for full statistics (EUR / month on this chart).
Salary analysis
Compared with the selected benchmark ("All roles in Remote - Global"), this listing's salary midpoint is about 93% lower. The offer sits below the benchmark range (€2,484–€14,831). The listed pay band (€463–€728) is tighter than the benchmark, which suggests lower salary variability. This benchmark is based on 479 comparable listings.
| Market | Lower bound (25th percentile) | Median | Upper bound (75th percentile) |
|---|---|---|---|
| All roles in Remote - Global | €2,484/per month | €7,145/per month | €14,831/per month |
| This job's pay range — not quoted in ad (Senior) | €463/per month | €595/per month | €728/per month |
About Apheris\nAt Apheris, we are building the future of how AI is applied in pharmaceutical R&D. We enable leading pharmaceutical teams to discover and develop drugs faster. We host the industry’s largest federated data networks for drug discovery AI, spanning co-folding, ADMET, and antibody developability. Across these networks, models are trained on proprietary industry datasets to achieve higher performance and broader applicability while keeping data control and IP protected. We deliver these superior models through drug discovery applications that enable teams to run them at scale, further customize them, and integrate them into existing R&D workflows. AI Structural Biology (AISB) Network: Pharmaceutical companies collaborate in the field of co-folding, structure-based binding affinity predictions and antibody design. ADMET Network: Pharmaceutical and biotech companies collaborate to improve small-molecule property prediction and expand into further drug modalities. Antibody Developability Network: Pharma partners collaborate to federate historical and purpose-built antibody developability data sets for secure ML training, without data leaving each partner’s environment.\nAbout the role\nWe are looking for a Senior Machine Learning Research Engineer to help drive the research and development of machine learning models for molecular and structural biology.\nThis is a hands-on role at the intersection of foundation models, structural biology, and federated learning. You\'ll execute research projects, turning ambitious scientific goals into frontier ML models that can be evaluated, released, and used in real drug-discovery workflows.\nAbout you\nWhat you will do\nWhat we expect from you\nNice to have\nWhat we offer you\nLogistics\nOur mission statement
Job Details
Responsibilities
- Develop and improve ML models in molecular and structural biology
Requirements
- PhD or MSc in ML, computational biology, computational chemistry, bioinformatics, physics or related field
Skills & Technologies
Education Level
No degree required
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