Senior ML Scientist, Multimodal Biotech Foundations

Altos Labs; Redwood City (CA); On-site; USD 201,000 - 330,000; Full time

Job summary

Altos Labs in Redwood City, CA seeks a Staff Machine Learning Scientist to design, build, and scale state-of-the-art foundation models for multiscale biology. You will join multidisciplinary teams across the Institute of Computation to advance aging and disease interventions, partnering with scientists and engineers.

You’ll pre-train and fine-tune large-scale systems, integrate LLMs with GNNs, develop Relational Foundation Models, and help productionize research with scalable data pipelines and

Qualifications

• PhD in Computer Science, Machine Learning, or quantitative field required.
• Minimum 5+ years of relevant work experience in academia or industry.
• Strong programming skills in Python and DL libraries (PyTorch, JAX, HF Transformers).
• Experience with multi-GPU and distributed training (DDP, DeepSpeed, Megatron, Ray).
• Proven track record of published AI/ML research at top-tier conferences.

Responsibilities

• Design, develop, and evaluate state-of-the-art foundation models at scale.
• Architect hybrid models that combine LLMs with Graph Neural Networks for reasoning over biological graphs.
• Develop Relational Foundation Models for zero-shot predictions on heterogeneous datasets.
• Lead efficient data loading and distributed training strategies across GPU nodes.
• Mentor junior staff and contribute to peer-reviewed research.

Skills

Python

PyTorch

Distributed training

GNNs

Deep learning

Communication

Education

PhD in Computer Science / ML

5+ years relevant work experience

Tools

DeepSpeed

Megatron

Ray

JAX

Hugging Face Transformers/Accelerate

Job description

Altos Labs in Redwood City, CA seeks a Staff Machine Learning Scientist to design, build, and scale state-of-the-art foundation models for multiscale biology. You will join multidisciplinary teams across the Institute of Computation to advance aging and disease interventions, partnering with scientists and engineers.

You’ll pre-train and fine-tune large-scale systems, integrate LLMs with GNNs, develop Relational Foundation Models, and help productionize research with scalable data pipelines and