Education: Doctorate
Experience: 2+ years
- Develop and advance machine learning methods for synthesis-aware molecular design across retrosynthesis, synthesis planning, molecular generation, and search in synthesizable chemical spaces.
- Integrate proprietary reaction and biochemical data to design the next generation of synthesis-aware models and workflows for hit finding and optimisation.
- Build robust, scalable pipelines for active-learning loops that interface directly with automated and high-throughput synthesis platforms.
- Design novel batch synthesis-planning algorithms that maximise chemical-space coverage, information gain and experimental efficiency.
- Drive scientific impact through publications, open-source releases, and conference talks.
- Collaborate widely with computational and experimental researchers at Roche and with academic partners.
- You bring deep machine-learning expertise with a strong foundation in linear algebra, probability and optimization, and hands-on experience in modern machine learning approaches such as graph-neural networks, sequence/language models and reinforcement learning.
- You are familiar with chemistry concepts relevant to synthesis planning and molecular optimisation as well as small molecule data and cheminformatics toolkits such as RDKit or Openeye.
- You are fluent in Python and have experience with modern ML frameworks like PyTorch or JAX as well as scientific software development.
- You hold a PhD or equivalent research depth in machine learning, computational chemistry, chemical engineering or a related quantitative field such as physics or statistics, with up to 2 years of industry research experience (Scientist) or 2+ years of industry research experience (Senior Scientist).
- You have a record of scientific excellence evidenced by journal and conference publications or a public portfolio of relevant projects (e.g. hosted on GitHub/GitLab)..
- Experience with retrosynthesis or synthesis-planning models.
- Experience with automated/high-throughput synthesis.
If designing molecules that move from screen to synthesis to patients excites you, apply now and help build self-driving discovery at Roche.
The expected salary range for this position, based on the primary location of San Francisco, is $147,600 - $274,000 for the ML Scientist, and $167,400 - 310,800 for the Senior ML Scientist. For the primary of location of New York City, $141.100 - $262,100 for the ML Scientist, and $160,100 - 297,300 for the Senior ML Scientist.
Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.
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This posting was published by Roche on their own careers system and is shown here with a direct link to apply there. Employers: for corrections or removal, contact jobs@veritahire.com.