About Altos Labs
Our mission at Altos Labs is to restore cell health and resilience through cellular rejuvenation programming to reverse disease, injury, and the disabilities that can occur throughout life. We are building a company where exceptional scientists and industry leaders from around the world work side by side to advance a shared mission, focusing on Belonging so all employees feel valued for their unique perspectives.
About the Role
As a Senior Machine Learning Engineer, you will be instrumental in implementing large-scale machine learning algorithms and systems and applying them to biological datasets. You will be responsible for developing new statistical and machine learning-based methods to analyze biological data, generating insights into cell health and rejuvenation. This role involves significant collaboration with world-class biologists and contributing computational thinking to Altos's mission and challenges, from modeling biological phenomena to enhancing our research culture through computation and AI.
Responsibilities
- Implement large-scale machine learning algorithms and systems and their application to biological datasets.
- Preprocess and clean data for machine learning model input.
- Train and optimize machine learning models on large, complex datasets.
- Develop new statistical and machine learning-based methods for analyzing biological data to produce biological insights about cell health and rejuvenation.
- Partner with world-class biologists across Altos to help generate biological insights with the goal of developing therapies.
- Help create machine learning-based computational tools to support biological and biomedical research at Altos.
- Bring computational thinking to bear on Altos’ mission and challenges, ranging from modeling biological phenomena to supporting Altos's research process and culture at Altos through computation and AI.
- Continuously learn and stay up-to-date on the latest developments in deep learning for biological discovery.
Qualifications
- Masters or Ph.D. degree in Computer Science or a related field, with a publication track record.
- Very strong programming skills, including experience with Python and deep learning libraries such as TensorFlow or PyTorch.
- Strong understanding of machine learning concepts, including model training, generalization, and optimization.
- Experience with machine learning and deep learning applied to noisy large-scale real-world datasets.
- Experience with large-scale tabular, image, and sequence data.
- Experience with distributed machine learning.
Who You Are
- Proven track record leveraging machine learning to solve real-world problems.
- Expertise in a subset 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.
- Expertise in computational infrastructure for deep learning, including GPUs, TPUs, cloud-based machine learning.
- Experience with modern machine learning frameworks like PyTorch, TensorFlow, or similar.
- Excellent communicator, able to convey technical concepts to diverse audiences.
- Brings a can-do attitude, curiosity, and creativity to problems and opportunities.
- Attentive to detail with excellent time management, multi-tasking, and prioritization skills.
- Thrives in collaborative environments, thinks pragmatically, works flexibly, and uses good judgment.
- Committed to fostering an inclusive work environment.
- Excitement about Altos's mission of investigating cellular rejuvenation programming to restore cell health and resilience.
- Deep analytical thinker and problem solver.
- Team player, focused on team success.
- Growth mindset, eager to expand skillset and knowledge in biology, computational science, and medicine.