ML Engineer - Scaling
Core
Build, optimize, and scale real-world applications of bio foundation models for drug discovery, enabling pharma and biotech teams to run millions of virtual experiments.
Role type
Senior Machine Learning Engineer (Infrastructure & Scaling)
Builds
Scalable training/inference pipelines, production-grade ML systems, and core ML infrastructure for bio foundation models.
Domain
Biotechnology / Drug Discovery / AI Infrastructure
Deliverable
production ML models
Required skills
Python, PyTorch, JAX, TensorFlow, MLOps, Transformers, Diffusion Models, SSMs, distributed compute, experiment tracking
Preferred skills
Open-source contributions, model compression, serving at scale, API integration
Technologies
Weights & Biases, Ray, Docker, Transformers, SSMs
Responsibilities
Build and maintain scalable training/inference pipelines; Optimize model performance, latency, and throughput; Design modular, reusable ML components; Collaborate with researchers to scale notebooks into production-grade systems; Own ML infrastructure components (data loading, distributed compute, experiment tracking).
Seniority
Senior, hands-on IC
