Research scientist machine learning health sciences

Senior / Principal Machine Learning Scientist
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 .
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. 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 emphasizes teamwork, transparency, scientific excellence, originality, rigor, and integrity.
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
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
Able to advise others across the wider function / company on cutting‑edge practices and approaches to enable the science / research. 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
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 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; 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 mechanistic/ML models
Proven experience applying sophisticated ML techniques to molecular and cell biological data sets (e.g., Experience in cell health and rejuvenation related research area
Experience in the application of machine learning methods to biological data
Experience in computational approaches to drug discovery
Experience with software development methodologies and open‑source software
Senior Scientist I, Machine Learning: $280,500 - $379,500
Senior Scientist II, Machine Learning: $317,050 - $428,950
Principal Scientist, Machine Learning: $376,550 - $509,450
Senior Scientist I, Machine Learning: $260,950 - $353,050
Senior Scientist II, Machine Learning: $285,600 - $386,400
Principal Scientist, Machine Learning: $340,000 - $460,000
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We value collaboration and scientific excellence. We believe that diverse perspectives and 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. 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. 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.
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