Senior ML Engineer: Frontier AI for Biology & Science

Biohub; New York (NY); Híbrido; USD 214.000 - 301.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

401(k) match

Paid time off

Relocation support

Descripción de la vacante

Biohub is building a general-purpose system to accelerate scientific discovery by integrating frontier AI models, biology foundations, and lab capabilities. As an ML Engineer, you will help connect everything and determine what science becomes possible.

You'll train and fine-tune biological foundation models, diagnose training bottlenecks, and design reusable libraries for researchers and engineers. This is a fast-paced, impactful role.

Formación

• Train, fine-tune, and evaluate biological foundation models and diagnose training problems.
• Design libraries and abstractions for researchers and engineers to reuse.
• Build large-scale data pipelines and monitor model/dataset versions.

Responsabilidades

• Work with researchers to train, fine-tune, and evaluate biological foundation models and diagnose training problems.
• Help evaluate and curate training and validation datasets at Petabytes scale.
• Design and create libraries and abstractions that researchers and engineers build on.
• Optimize GPU-native data loading for large tensor workloads and resolve hardware utilization bottlenecks across backends.
• Build and maintain reliable distributed pre and post training systems.
• Support production deployment, with tracking of model and dataset artifacts throughout the ML lifecycle.
• Improve model and cluster monitoring, unit and integration testing, and continuous integration.
• Work with partner researchers and engineers to deploy models and supporting infrastructure in external environments.

Conocimientos

Python

PyTorch

CUDA

Distributed training

Performance optimization

Data pipelines

Herramientas

Slurm

Docker

Kubernetes

Descripción del empleo

Biohub is building a general-purpose system to accelerate scientific discovery by integrating frontier AI models, biology foundations, and lab capabilities. As an ML Engineer, you will help connect everything and determine what science becomes possible.

You'll train and fine-tune biological foundation models, diagnose training bottlenecks, and design reusable libraries for researchers and engineers. This is a fast-paced, impactful role.