Onepot AI offers automated synthesis of small molecules from basic building blocks using a unified, end-to-end process. It generates around fifty distinct compounds in a single workflow, eliminating the need for bespoke methods for each target. Backed by Speedinvest.
About the role
In this position, you will help train the next generation of chemistry models, and enable synthesis of previously inaccessible molecules. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Strong fundamentals in machine learning with a deep understanding of modern empirical/experimental ML
- Experience developing novel model training techniques or dealing with novel tasks or datasets
- Experience in a startup, research group, competition team, or other environment where you had significant ownership and limited resources is particularly relevant
- Familiarity with PyTorch or other machine learning frameworks
- Knowledge of basic machine learning theory
- Enthusiasm about working across the entire machine learning stack (data, training, inference, deployment)
More about this role
onepot is automating chemistry. Our goal is to enable a self-improvement loop for chemistry by combining AI and advanced robotics. In this loop, AI systems design experiments, robotic systems execute them, and the resulting data improves the next generation of models.
This goal can only be achieved by bringing together people from different backgrounds: ML engineers, chemists, computer scientists, and hardware engineers. We are building a small, unusually ambitious team and are looking for a machine learning researcher to join us to help train the next generation of chemistry models.
We train models for a wide range of tasks, including reaction planning and outcome, input material costs, and mass spectra prediction. Most of these models are state-of-the-art; many are trained on proprietary datasets that are larger, and higher quality, than what exists in the literature.
Our models are primarily deployed internally for real workflows. As such, we maintain a tight feedback loop between usage, data, and model training.
In this position, you will help train the next generation of chemistry models, and enable synthesis of previously inaccessible molecules.
Your work will span the full...
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