Foundation Models ML Engineer for Molecular AI (Equity)

Genesis Molecular AI; New York (NY); On-site; USD 150,000 - 230,000; Full time

Benefits offered by this job

Equity

Health benefits

401(k)

Unlimited PTO

Meals provided

Family leave

Disability insurance

Job summary

Genesis Molecular AI is seeking an ML Research Engineer to lead the engineering pillar for foundation models in molecular science. You will scale, ship, and productionize models that power drug discovery programs, partnering with researchers, chemists, and biologists.

You'll own the end-to-end lifecycle from pretraining to deployment, optimize distributed training and inference, and mentor other engineers while publishing work at top conferences.

Qualifications

• 2+ years industry experience building complex ML systems.
• Proven track record of shipping high-performance Python/PyTorch code and distributed training systems.
• Experience with training models at scale on large datasets and GPUs.

Responsibilities

• Drive the development and scaling of foundation models for molecular science.
• Implement, optimize, and productionize models from research prototypes.
• Optimize distributed training, inference, and GPU performance.
• Engage with literature and build new architectures for deployment.
• Bridge ML research with computational chemistry workflows to enable drug discovery.
• Help productionize Pearl and related structure prediction models for reliable deployment.
• Own the experimental lifecycle and drive data-informed iteration.
• Ship state-of-the-art models to production.
• Collaborate with scientists to integrate models into drug discovery platforms.
• Mentor researchers and engineers to uphold high-quality code and rigorous experimentation.
• Contribute to the research community via publications.

Skills

Python

PyTorch

PyTorch Lightning

Ray

CUDA

Distributed Training

Foundation Models

Education

MS or PhD in ML/CS

Tools

PyTorch Geometric

Triton

TensorRT

Job description

Genesis Molecular AI is seeking an ML Research Engineer to lead the engineering pillar for foundation models in molecular science. You will scale, ship, and productionize models that power drug discovery programs, partnering with researchers, chemists, and biologists.

You'll own the end-to-end lifecycle from pretraining to deployment, optimize distributed training and inference, and mentor other engineers while publishing work at top conferences.