Senior Data Engineer

5 days ago

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Apheris

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Apheris is a company that specializes in enabling secure and compliant data collaboration across distributed data environments, particularly for enterprises. The company's solutions empower organizations to engage in federated machine learning and analytics, facilitating the building of models without needing to move sensitive data, thus preserving privacy and security. Apheris focuses on providing technology that allows multi-party data ecosystems and partnerships, with a strong emphasis on compliance, particularly in regulated industries like pharmaceuticals and biotech. Their technology is trusted by major pharmaceutical companies to support AI-driven drug discovery initiatives without compromising proprietary data.

ML • Deep Learning • Privacy • Biomedical data • NLP

11 - 50 employees

Founded 2019

🤖 Artificial Intelligence

🧬 Biotechnology

💊 Pharmaceuticals

📋 Description

• ADMET Data Pipeline Development: Design, build and maintain scalable pipelines for ingesting, processing, and harmonizing diverse ADMET datasets from public sources (e.g., ChEMBL, PubChem) and proprietary assays. • Data Harmonization: Standardize heterogeneous ADMET data formats (e.g., in vitro assays, in silico predictions) across network participants to enable modelling readiness of the data. • Model-Ready Dataset Curation: Preprocess raw ADMET data (e.g., normalizing units, handling missing values) to support AI/ML model training for a variety of endpoints (like bioavailability, hERG inhibition, or CYP450 interactions). • Data Quality Assurance: Implement and automate validation checks to ensure ADMET data integrity. • Cross-Functional Integration: Work with computational chemists to optimize data structures for AI-driven ADMET models (e.g., graph-based representations for metabolic pathways). • Work with our customers and potentially academic partners to define data preprocessing, selection, and benchmarking strategies for novel training tasks involving ADMET data, including leveraging and harmonizing assay data from different sources. • Collaborate cross-functionally to ensure data and resulting models address real-world drug discovery needs. • Mentor and guide team members on a content level, supporting the planning and breakdown of complex ADMET data preparation. • Influence strategic decisions on data infrastructure and data quality assurance. • Contribute to publications or open-source contributions where relevant.

🎯 Requirements

• You have a background in computational chemistry, cheminformatics, computational biology, bioinformatics, data engineering or computer science, and a track record of preparing data for ML models addressing real-world drug discovery problems. • You have deep experience in pharma/biotech ADMET data pipelines for machine learning. • You have deep experience in ADMET data, including an understanding of assay protocols and how to map protocols to each other. • You’re comfortable navigating complex technical landscapes and can break down and drive execution on ambitious modeling plans. • You understand how ADMET data and models are used in the drug discovery lifecycle and can align your work to practical use cases. • Bonus points if you have experience in federated learning, privacy-preserving ML, or secure model training. • You have experience in benchmarking predictive models against standardized datasets. • You have experience working with ML and MLOps systems at scale, including CI/CD, model versioning, Docker, Kubernetes, cloud platforms, and orchestration tools. • You’ve contributed to open-source data or cheminformatics tooling. • You have hands-on experience working with ADMET assays and DMPK stakeholders. • You have experience guiding technical direction in a fast-paced, research-oriented environment.

🏖️ Benefits

• Industry-competitive compensation, incl. early-stage virtual share options • Remote-first working – work where you work best, whether from home or a co-working space near you • Great suite of benefits, including a wellbeing budget, mental health benefits, a work-from-home budget, a co-working stipend and a learning and development budget • Regular team lunches and social events • Generous holiday allowance • Quarterly All Hands meet-up at our Berlin HQ or a different European location • A fun, diverse team of mission-driven individuals with a drive to see AI and ML used for good • Plenty of room to grow personally and professionally and shape your own role