Job Specifications
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.
For more information, see our website at altoslabs.com.
Our Value
Our Single Altos Value: Everyone Owns Achieving Our Inspiring Mission.
Diversity at Altos
We believe that diverse perspectives are foundational to scientific innovation and inquiry. 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 a Senior or Principal Machine Learning Scientist, you will play a prominent role in developing generative AI/ML models for multi-modal, multiscale biology from virtual cells to agentic target assessment. We are looking for a hands-on, creative, and collaborative individual to join our multidisciplinary team of scientists and engineers focused on transforming how we treat aging and disease. The successful candidate will thrive in a fast-paced environment that emphasises teamwork, transparency, scientific excellence, originality, rigor, and integrity.
Responsibilities
Pioneer novel machine learning methodologies and statistical frameworks (e.g., generative models, causal inference, diffusion models, and advanced transformer architectures) to address fundamental challenges in cell health and rejuvenation
Contribute to setting the long-term technical vision and research strategy for a core domain (e.g., multi-modal data fusion, perturbation modeling) within the Institute of Computation
Translate your deep understanding of the mathematical and theoretical underpinnings of cutting-edge AI research into high-impact applications
Design, implement, and optimize large-scale machine learning systems using modern frameworks (e.g., PyTorch, JAX) and agile practices
Develop and manage efficient distributed training strategies across multiple GPUs and compute clusters to handle terabytes of multi-modal biological data
Develop robust approaches for multi-modal data integration and cross-domain mapping to extract actionable biological insights
Apply computational thinking to solve problems in drug target identification, compound assessment, and prediction of cellular perturbation responses
Lead the full ML development lifecycle from theoretical conception and data strategy through model development, training, and evaluation
Act as a key technical mentor to Machine Learning Scientists and Engineers, raising the bar for scientific rigor and model robustness across the organization.
Who You Are
Proven track record leveraging machine learning to solve real-world problems;
Expertise in one or more of the following: generative models, language models, computer vision, bayesian inference, causal reasoning & inference, transfer & multi-task learning, diffusion models, graph neural networks, active learning, cooperative agents
Experience writing production-quality code with modern machine learning frameworks such as PyTorch, TensorFlow, JAX, or similar
Experience with multi-GPU and distributed training at scale
A team player who thrives in collaborative environments and is committed to enabling colleagues to reach their full potential through giving and requesting feedback focussed on professional growth
Able to advise others across the wider function / company on cutting edge practices and approaches to enable the science / research. Desire to constantly expand your skillset and knowledge. Keen to learn more about biology, computational science, and medicine;
Inspired by the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities.
Minimum Qualifications
Ph.D. in Machine Learning, Computer Science, Artificial Intelligence, Statistics, or a related quantitative field, demonstrating a deep theoretical foundation in ML/AI.
6+ years of of relevant post-PhD work experience in either an academic or industry setting
Proven experience developing and applying complex machine learning models, preferably with a significant portion of that time spent in a fast-paced industry or translational research environment.
A strong track record of leading and publishing innovative, peer-reviewed research in top-tier ML conferences (e.g., NeurIPS, ICML, ICLR) or high-impact scientific journals.
Excellent scientific communication skills: verbally and in writing; with computational and non-computational audiences, in informal 1-1 settings, team meetings, and formal seminars
Expertise in several of the following: deep learning, reinforcement learning, generative models, language models, computer vision, Bayesian inference, causal reasoning & inference, transfer & multi-task learning, graph neural networks, active learning, hybrid mechan
About the Company
Altos Labs is a biotechnology company focused on restoring cell health and resilience through cell rejuvenation to reverse disease, injury, and the disabilities that can occur throughout life. The company comprises a community of leading scientists, clinicians, and leaders from academia and industry working together towards this common mission.
Altos operates in the San Francisco Bay Area, San Diego and Cambridge, UK.
Note: Altos Labs will not ask you to download a messaging app for an interview or spend your own money to...
Know more