Senior Scientist, Machine Learning

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

Our Mission

Our mission is to restore cell health and resilience through cell rejuvenation to reverse disease, injury, and the disabilities that can occur throughout life.

Diversity at Altos

Altos Labs has been named one of the Top 3 Biotech Companies and ranked for the second year on the Forbes 2026 Best Startups in America list. At Altos, exceptional scientists and industry leaders from around the world work together to advance a shared mission. Our intentional focus is on Belonging, so that all employees know that they are valued for their unique perspectives. We are all accountable for sustaining a diverse and inclusive environment.

What You Will Contribute To Altos

As part of our team, you will help to accelerate and optimize our progress in developing unified, multi-modal generative foundation models for multiscale biology. You will be an integral part of our multidisciplinary teams building the computational platforms that will enable Altos to achieve its mission.

In this role, you will partner and collaborate with other multidisciplinary Scientists and Engineers across the Institute of Computation to design, build, and scale state-of-the-art foundation models that tackle biological questions and aid in the discovery of novel interventions for aging and disease. You will focus on the synthesis of unstructured multimodal signals with the structured relational data and knowledge graphs that represent biological reality.

The successful candidate will thrive in a fast-paced environment that stresses teamwork, transparency, scientific excellence, originality, and integrity.

Responsibilities

As a Staff Machine Learning Scientist, you will use your experience to focus on designing, developing, and evaluating state-of-the-art foundation models, at scale, to benefit the research.

• Pre-train and fine-tune large-scale machine learning systems using multimodal biological data, natural language, and structured relational inputs.
• Architect and implement novel hybrid models that integrate Large Language Models (LLMs) with Graph Neural Networks (GNNs) for multi-hop reasoning over biological knowledge graphs.
• Develop Relational Foundation Models (RFMs) that enable zero-shot predictive tasks over heterogeneous, multi-table biological datasets.
• Lead the design of efficient data loading strategies and distributed training recipes (e.g., FSDP, DeepSpeed) to train models across multiple GPU nodes.
• Gain insights into model performance based on theory, deep research, and the mathematical underpinnings of set-invariant and graph-structured architectures.
• Apply strong coding experience to model development and deployment, ensuring research prototypes transition into reliable, scalable production systems.
• Stay up-to-date on the latest developments in deep learning—including native early-fusion and Mixture-of-Experts (MoE) architectures—and apply this knowledge to Altos' research.
• Mentor junior staff while maintaining a high individual technical contribution to the core research ecosystem and peer-reviewed publications.

Who You Are

We are looking for someone who is:

• Excited about the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities.
• Highly collaborative in mindset and ways of working across research and engineering boundaries.
• Self-motivated to drive and deliver on long-term technical projects and scientific goals.
• Demonstrates the desire to grow professionally and expand your skillset in biology, machine learning, and/or drug development.
• Able to communicate and explain the design, results, and impact of complex AI architectures to both scientific and non-scientific staff.
• Keen to contribute to seminars and scientific initiatives within Altos and the broader AI research community.

Minimum Qualifications

• PhD in Computer Science, Machine Learning, or a similar quantitative field with 5+ years of relevant work experience in academic or industry settings.
• Prior experience in developing and implementing novel generative AI models, specifically in multimodal integration, GraphRAG, or relational deep learning.
• Deep understanding of Machine Learning principles and how they apply to diverse architectures like Transformers, GNNs, and diffusion models.
• Very strong programming skills in Python and deep learning libraries (e.g., PyTorch, JAX, Hugging Face Transformers/Accelerate).
• Proven experience with multi-GPU and distributed training at scale (e.g., DDP, FSDP, DeepSpeed, Megatron, or Ray).
• Strong track record of published, peer-reviewed innovative AI/ML research at top-tier conferences (NeurIPS, ICML, ICLR, CVPR).

Preferred Qualifications

• Familiarity with tabular foundation models (e.g., TabPFN) and in-context learning strategies for structured data.
• Specific experience in native multimodal modeling (early-fusion) or the synthesis of LLMs and Knowledge Graphs.
• Track record of ML applied to biological data, such as NGS data (RNA-seq, ATAC-seq), biological imaging (microscopy, IF), or spatial transcriptomics.
• Experience in optimizing large-scale inference via quantization, distillation, or memory-efficient attention mechanisms.

The salary range forRedwood City, CA:

• Scientist I, Machine Learning: $200,900 - $257,500
• Scientist II, Machine Learning: $226,200 - $290,000
• Senior Scientist I, Machine Learning: $257,400 - $330,000

The salary range forSan Diego, CA:

• Scientist I, Machine Learning: $179,400 - $230,000
• Scientist II, Machine Learning: $212,900 - $273,000
• Senior Scientist I, Machine Learning: $239,500 - $307,000

Exact compensation may vary based on skills, experience, and location.

Equal Opportunity Employment

We value collaboration and scientific excellence.

We believe that a culture of belonging are foundational to scientific innovation and inquiry. At Altos Labs, exceptional scientists and industry leaders from around the world work together to advance a shared mission. Our intentional focus is on Belonging, so that all employees know that they are valued for their unique perspectives. We are all accountable for sustaining an inclusive environment.

Altos Labs provides equal employment opportunities to all employees and applicants for employment, without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Altos prohibits unlawful discrimination and harassment. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

Thank you for your interest in Altos Labs where we strive for a culture of scientific excellence, learning, and belonging.