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Roche
Roche
H1B Visa SponsorConsultingFood & BeverageHealthcare
Roche is a global healthcare company combining pharmaceutical research and development with diagnostic testing and digital health. Its work focuses on improving patient outcomes through earlier detection, more targeted treatments, and science-led innovation, including AI-enabled tools. The company develops solutions for complex diseases such as cancer and neurological conditions while working with healthcare systems, research partners, and other stakeholders around the world.
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Senior Machine Learning Scientist, Synthesis Planning and Optimization

Develop machine learning models for synthesis-aware molecular design, planning, generation, and optimization. Build automated synthesis workflows supporting Roche’s AI-driven drug discovery research.

USUnited StatesCACaliforniaNYNew York
$147,600 – $274,000 / year
On-siteFull-timeSeniorEnglish RequiredMachine Learning Engineer
PythonPyTorch

Description

  • Advance machine learning methods for synthesis-aware molecular design, including retrosynthesis, synthesis planning, molecular generation, and search across synthesizable chemical spaces.
  • Combine proprietary reaction and biochemical data to create synthesis-aware models and workflows for hit discovery and optimization.
  • Develop reliable, scalable active-learning pipelines that connect with automated and high-throughput synthesis platforms.
  • Create batch synthesis-planning algorithms that improve chemical-space coverage, information gain, and experimental efficiency.
  • Contribute to scientific progress through publications, open-source projects, and conference presentations.
  • Partner with computational and experimental scientists at Roche and with external academic collaborators.
  • Develop machine learning approaches that generate synthesizable molecules and link generative design with automated synthesis.

Requirements

  • Advanced machine learning expertise grounded in linear algebra, probability, and optimization.
  • Practical experience with graph neural networks, sequence or language models, and reinforcement learning.
  • Working knowledge of chemistry concepts used in synthesis planning and molecular optimization.
  • Experience handling small-molecule datasets and using cheminformatics tools such as RDKit or OpenEye.
  • Proficiency in Python.
  • Experience with contemporary machine learning frameworks, including PyTorch or JAX.
  • Background in scientific software development.
  • PhD or comparable research experience in machine learning, computational chemistry, chemical engineering, physics, statistics, or a related quantitative discipline.
  • Up to two years of industry research experience for Scientist level, or more than two years for Senior Scientist level.
  • Evidence of scientific excellence through journal or conference publications, or a public portfolio of relevant work.
  • Preferred: Experience developing retrosynthesis or synthesis-planning models.
  • Preferred: Experience with automated or high-throughput synthesis.

Benefits

  • A discretionary annual bonus may be offered based on individual and Company performance.
  • Benefits are described at the provided link.

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