Senior Developer Relations Lead, AI-Enabled Drug Discovery Science
$224k - $431k • Remote • US, CA, Santa Clara
Posted 1mo ago
Job Location
US, CA, Santa Clara
Tech Stack
Remote Work Policy
Fully remote
Categories
Machine Learning Engineer
About the job
NVIDIA is seeking a leader in AI-enabled drug discovery science to coordinate research and development efforts. This role bridges RNA therapeutics, experimental data generation, computational modeling, and translational science. The ideal candidate is a hands-on researcher experienced in guiding scientific teams, making technical trade-offs, and ensuring alignment across experimental, data, model, and compute activities. You will be responsible for converting scientific objectives into executable plans, leading workstreams in data curation, machine learning, and platform engineering, and guiding closed-loop learning processes. This position requires establishing robust science-stream governance and providing clear reporting on progress, dependencies, and risks to program leadership.
Responsibilities
- Coordinate the operating plan across research priorities, execution, and program achievements.
- Convert scientific therapeutic objectives into executable plans.
- Lead workstreams spanning data curation & analysis, machine learning, automation, and platform engineering.
- Collaborate on assay and readout strategies for AI-prepared data.
- Guide closed-loop learning across AI-generated hypotheses, automated experiments, and model updates.
- Review science validity for key biology applications.
- Establish science-stream governance, including reviews, decision logs, and risk tracking.
- Report on workstream progress, critical decisions, dependencies, resource needs, and unresolved risks.
Requirements
- PhD in life sciences, therapeutic discovery, chemical biology, molecular pharmacology, computational biology, bioengineering, or related field, or equivalent experience.
- 12+ years of research or drug-discovery experience in therapeutic discovery or platform biology.
- Deep understanding of therapeutic development and translational biology.
- Experience leading large interdisciplinary teams combining experimental science, computational modeling, and data analysis.
- Proven track record of leadership in matrixed environments.
- Proficiency with high-content and high-throughput data generation and validation.
- Ability to collaborate with AI and infrastructure teams on model requirements and experimentation.
Benefits
- Equity
- Benefits