Scientist II, Machine Learning

As a Machine Learning Scientist, you will play a prominent role in developing generative AI/ML models for multi-modal, multiscale biology. We are looking for a hands-on, creative and collaborative person 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

• Partner with world-class scientists across Altos to help generate biological insights with the goal of developing novel therapies;
• Design and implement large-scale machine learning algorithms and systems applied to biological datasets;
• Train, evaluate, and optimize machine learning models at scale;
• Communicate effectively with internal and external collaborators to meet ambitious research and development goals.

• 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; 
• 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;
• Growth mindset - the desire to constantly expand your skillset and knowledge. Keen to learn more about biology, computational science, and medicine;
• Excitement about the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities.

• Ph.D. degree in a quantitative/computational field such as computer science, artificial intelligence, mathematics, statistics, physics, or computational biology, or equivalent experience;
• Relevant postgraduate industry and/or academic work experience;
• Experience in developing and using machine learning models; such as representation learning, self-supervised learning and generative models to analyze large data sets to make data-driven recommendations and support scientific inquiry.
• Very strong programming skills, including experience with Python and deep learning libraries such as PyTorch or JAX
• Ability to communicate and explain the design, results, conclusions and the impact of findings to both scientific and nonscientific staff.

• Experience in cell health and rejuvenation-related research area;
• Familiarity with biological data formats, concepts, and computational models;
• Experience in the application of machine learning methods to biological data, including genomics, transcriptomics, epigenetics, proteomics, and imaging;
• Experience with identification and assessment of drug targets and/or therapeutic compounds;
• Track record of high-caliber scientific work, e.g., demonstrated through impactful publications in peer-reviewed scientific journals or major ML conferences;
• Track record in open-source software development, e.g., demonstrated by high-impact GitHub repository.

For UK applicants, before submitting your application:

- Please click here to read the Altos Labs EU and UK Applicant Privacy Notice (bit.ly/eu_uk_privacy_notice)
- This Privacy Notice is not a contract, express or implied and it does not set terms or conditions of employment.

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