Rocket - Think it. Type it. Launch it.
Mini tools
South San Francisco, California, United States
At Atomic AI, we build artificial intelligence to pioneer new frontiers in drug discovery. Our unique R&D platform, an early version of which was featured on the cover of Science, provides new strategies to treat previously undruggable diseases by targeting RNA. We continue to advance this platform by developing new machine learning methods and unique foundation models fueled by our large-scale, in-house experimental data collection. We are an interdisciplinary team of scientists and engineers and believe our people are our greatest strength and the key to our success.
Scientist, Machine Learning
Atomic AI
On-site
San Francisco, CA, United States
Full-time
$170,000 -
$230,000
About Atomic AI
About the Role
As a full-time Scientist on the Machine Learning team, you will work closely with engineers and experimental scientists to advance our technology platform for RNA structure prediction, target identification, and early drug discovery. You will co-lead the development and evaluation of the machine learning pipeline. You will contribute new ideas and realize their potential as part of a continuously advancing state-of-the-art platform. You will proactively shape the directions of the machine learning efforts and those of the whole company.
Qualifications
Ph.D., M.Sc., or M.Eng. in Computer Science, Physics, Applied Mathematics, Materials Science, Computational Biology, or related field.
4+ years of experience developing machine learning methods for scientific applications.
Foundational knowledge of machine learning and underlying mathematical concepts.
Proficiency in Python and deep learning frameworks (e.g., JAX, PyTorch).
Excellent presentation and writing skills, able to clearly communicate technical information to colleagues.
Pluses:
Publications at major machine learning conferences or in major scientific journal.
Research experience related to structural biology, molecular design, and drug discovery.
Foundational knowledge of physics, chemistry, and molecular biology.
Demonstrated ability to develop performant code.
4+ years of experience developing machine learning methods for scientific applications.
Foundational knowledge of machine learning and underlying mathematical concepts.
Proficiency in Python and deep learning frameworks (e.g., JAX, PyTorch).
Excellent presentation and writing skills, able to clearly communicate technical information to colleagues.
Pluses:
Publications at major machine learning conferences or in major scientific journal.
Research experience related to structural biology, molecular design, and drug discovery.
Foundational knowledge of physics, chemistry, and molecular biology.
Demonstrated ability to develop performant code.
Responsibilities
Design and develop novel machine learning models for RNA structure prediction and drug targeting.
Evaluate and advance the state of the art of our structure prediction platform.
Collaborate with our wetlab team on the targeted acquisition of experimental data to improve our machine learning models.
Develop high-quality code in a team setting.
Analyze, interpret, and organize results and present progress to colleagues in regular research meetings.
Work within a collaborative, high-caliber, interdisciplinary team and proactively shape the scientific and strategic vision of the company.
Evaluate and advance the state of the art of our structure prediction platform.
Collaborate with our wetlab team on the targeted acquisition of experimental data to improve our machine learning models.
Develop high-quality code in a team setting.
Analyze, interpret, and organize results and present progress to colleagues in regular research meetings.
Work within a collaborative, high-caliber, interdisciplinary team and proactively shape the scientific and strategic vision of the company.
