ML Scientist: Scientific Reasoning for Drug Discovery
Genentech
New York (NY)
On-site
USD 141,100 - 262,100
Full time
14 days+
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Benefits offered by this job
Discretionary annual bonus
Comprehensive benefits package
Job summary
A leading biotechnology company seeks a Machine Learning Scientist to join its AI for Drug Discovery team in New York City. This role focuses on designing and implementing cutting-edge machine learning systems aimed at enhancing drug discovery through the use of large language models and advanced reasoning techniques. Candidates should have a strong educational background in a quantitative field, relevant work experience, and a record of excellence in research, all while collaborating with experts to turn prototypes into scalable solutions. Competitive salary and benefits offered.
Qualifications
2+ years of relevant work experience or Ph.D. with 0-2 years relevant work experience.
Experience developing and training large-scale machine learning models.
Strong publication record in top-tier venues.
Responsibilities
Design and implement large-scale machine learning systems.
Collaborate closely with researchers to translate ideas into production systems.
Develop and improve model performance on scientific tasks.
Skills
LLM Expertise
Strong software engineering skills
Experience with high-performance computing systems
Education
BS/MS in Computer Science, Statistics, Mathematics or related field
Ph.D. in relevant field
Job description
A leading biotechnology company seeks a Machine Learning Scientist to join its AI for Drug Discovery team in New York City. This role focuses on designing and implementing cutting-edge machine learning systems aimed at enhancing drug discovery through the use of large language models and advanced reasoning techniques. Candidates should have a strong educational background in a quantitative field, relevant work experience, and a record of excellence in research, all while collaborating with experts to turn prototypes into scalable solutions. Competitive salary and benefits offered.