Principal ML Engineer - Drug Discovery AI Leader

Placements24

Rustenburg

Hybrid

ZAR 1,200,000 - 2,400,000

Full time

28 hours ago
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Benefits offered by this job

Competitive salary
Medical insurance
Retirement plan
Learning opportunities

Job summary

Placements24 in Rustenburg, North West, invites a Principal Machine Learning Engineer to lead AI initiatives for drug discovery. You will architect and deploy ML models addressing molecular properties, bioactivity, and synthesis pathway design in a research-driven environment.

The role requires deep ML theory and hands-on production experience, collaboration with computational chemists, and mentoring of juniors.

Qualifications

  • Master's or PhD in a quantitative field with strong ML foundation.
  • 7+ years in ML engineering applying ML to scientific problems.
  • Experience building and deploying ML models in production.
  • Proficiency in Python and ML libraries; CI/CD and data pipelines knowledge.

Responsibilities

  • Lead design and deployment of ML models for drug discovery.
  • Develop models for molecular properties, bioactivity, ADMET.
  • Use TensorFlow/PyTorch and cheminformatics tools like RDKit.
  • Build robust data pipelines for large chemical/biological datasets.
  • Collaborate with chemists and medicinal chemists; mentor juniors.
  • Deploy models to production; ensure scalability and reliability.
  • Stay updated with ML and cheminformatics research; document findings.

Skills

ML expertise
Deep learning
Python
TensorFlow
PyTorch
Scikit-learn
Keras
Cloud AWS
Docker
Kubernetes

Education

Master's or PhD in CS/ML/Computational Chemistry

Tools

RDKit
Docker
Kubernetes
AWS
Azure

Job description

Placements24 in Rustenburg, North West, invites a Principal Machine Learning Engineer to lead AI initiatives for drug discovery. You will architect and deploy ML models addressing molecular properties, bioactivity, and synthesis pathway design in a research-driven environment.

The role requires deep ML theory and hands-on production experience, collaboration with computational chemists, and mentoring of juniors.

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