Machine Learning Researcher

Can machine learning help solve diseases?
Deep Origin is a biotechnology company accelerating drug discovery through machine learning and simulation. Our platform simulates biological systems, predicts their properties, and generates solutions to understand and modify the processes that cause diseases. Today, our best-in-class ML models are used across multiple projects targeting complex diseases. Our team computationally models biology from small molecules to the whole cell.

The ML models that will deliver the next breakthroughs in drug discovery have yet to be invented—and you will help create them. You will design and train large-scale ML models for biological systems while reading, understanding, and contributing to state-of-the-art research.

• Hands-on experience designing, implementing, and training large-scale ML models.
• Strong proficiency in PyTorch, transformer architectures, and the full ecosystem of modern deep learning.
• Deep understanding of optimization methodologies for ML models.
• Solid understanding of statistics, probability, and linear algebra.
• Strong software engineering practices (clean code, version control, testing).

We'd be excited if you have

• Publications in top-tier ML conferences and journals.
• Open-source contributions to machine learning libraries and scientific simulation frameworks.
• Experience developing robust ML models within low-data regimes and data-constrained environments.
• Achievements in IOI, IMO, IPhO, IChO, ICPC, IMC, or related Olympiads.
• Ph.D. in a relevant field.

• Collaborate with ML researchers and domain experts to design, develop, and implement ML models for drug discovery.
• Design and implement robust data processing and feature engineering pipelines.
• Develop benchmarks, evaluation protocols, and metrics to assess model performance.
• Stay at the forefront of the field by continuously reading, analyzing, and reproducing cutting-edge research.
• Write clean, efficient, and maintainable research and production-quality code.

• Health insurance for you and your family.
• Additional leave days added to your annual paid time off.
• Weekly highly specialized seminars on bio-machine learning and chemistry.
• Collaborating with highly experienced professionals.
• Salary with equity, including stock options, after probation.