We are seeking a Machine Learning Scientist to develop deep learning models for genomic information processing and functional inference. You will be part of an early-stage non-profit research startup that is driven by the mission to disrupt the way we interpret genomic data.
Responsibilities
- Design, implement, scale and analyze deep-learning models for genomic sequences.
- Deploy and maintain open-source models.
- Communicate research outcomes with visualizations and thorough documentation with the broader research community.
- Work closely with computational biologists to implement, analyze and benchmark novel architectures for genomic information processing and representation learning.
Qualifications
- Degree in Computer Science, Machine Learning, Statistics, Applied Math, or a related field (Ph.D. preferred)
- 5+ years experience in Machine Learning research with a track record developing novel techniques.
- Experience developing and deploying large models from scratch.
- Experience working with biological sequence data is a plus.
Knowledge, Skills and Abilities
- Deep theoretical understanding of geometric representation learning.
- Ability to efficiently scale large models and iterate rapidly.
- Proficiency with state-of-the-art deep learning frameworks and optimization techniques.
- Ability to work collaboratively in a multidisciplinary team of biologists and computer scientists.
Other Duties
Please note that this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities and activities may change at any time with or without notice.
Additional Notes
- This position can be fully remote, but we prefer candidates based in New York for a hybrid work model.