Senior ML Scientist — Multimodal Biotech Foundations

Altos Labs; San Francisco, San Diego (CA, CA); On-site; USD 200,000 - 330,000; Full time

Job summary

Altos Labs in Redwood City, CA is seeking a Staff Machine Learning Scientist to design, develop, and evaluate state‑of‑the‑art foundation models at scale for multiscale biology, collaborating with multidisciplinary scientists and engineers.

You will pre‑train and fine‑tune models on multimodal biological data, integrate LLMs with GNNs for reasoning over biological knowledge graphs, and mentor junior staff while contributing to peer‑reviewed publications.

Qualifications

• PhD in Computer Science, ML or related field with 5+ years of experience.
• Experience developing novel generative AI models for multimodal data.
• Deep understanding of ML principles across Transformers, GNNs, diffusion models.
• Strong Python and DL library skills (PyTorch, JAX, HF Transformers/Accelerate).
• Experience with multi-GPU and distributed training (DDP, FSDP, DeepSpeed, Megatron, Ray).
• Proven publication record in top AI conferences (NeurIPS, ICML, ICLR, CVPR).

Responsibilities

• Design, develop, and evaluate state-of-the-art foundation models at scale.
• Pre-train and fine-tune large-scale ML systems on multimodal data.
• Architect hybrid models combining LLMs with GNNs for biological knowledge graphs.
• Develop RFMs for zero-shot tasks over heterogeneous datasets.
• Lead data loading strategies and distributed training across GPUs.
• Mentor staff and contribute to peer‑reviewed publications.

Skills

Generative AI multimodal

GraphRAG/relational DL

Transformers/GNNs/diffusion models

Python programming

PyTorch/JAX/HF Transformers

Distributed multi-GPU training

Research publications

Communication skills

Education

PhD in Computer Science / Machine Learning

Tools

PyTorch

JAX

Hugging Face Transformers/Accelerate

DeepSpeed

Megatron/Ray

Knowledge Graphs

Job description

Altos Labs in Redwood City, CA is seeking a Staff Machine Learning Scientist to design, develop, and evaluate state‑of‑the‑art foundation models at scale for multiscale biology, collaborating with multidisciplinary scientists and engineers.

You will pre‑train and fine‑tune models on multimodal biological data, integrate LLMs with GNNs for reasoning over biological knowledge graphs, and mentor junior staff while contributing to peer‑reviewed publications.