About the Role
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, both 1:1 and as a presenter to multi-faceted audiences. Ability to communicate technical concepts to people less familiar with the field;
Brings a can-do attitude that approaches problems and opportunities with curiosity and creativity;
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 contributing to making the work environment inclusive and enabling colleagues to contribute to their full potential in pursuit of the organizational objectives;
Excitement about the Altos mission of investigating cellular rejuvenation programming to restore cell health and resilience, with the goal of reversing disease to transform medicine;
Deep analytical thinker and problem solver;
Team player - enjoys working on larger efforts with others and puts the success of their team above their own;
Growth mindset - the desire to constantly expand your skillset and knowledge. Keen to learn more about biology, computational science, and medicine;
Bonus: Experience in cell health and rejuvenation-related research area;
Bonus: Experience in the application of machine learning methods to biological data;
Bonus: Experience in computational approaches to drug discovery;
Bonus: Proven track record in open-source software development, e.g., demonstrated by high-impact GitHub repository;
Bonus: Proven track record of high-caliber scientific work, e.g., demonstrated through publications in peer-reviewed scientific journals.
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 the 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.
We are open and interested in having people at varying levels of experience:
The salary ranges for this position are: Senior ML Engineer £83,300 to £112,700; Staff ML Engineer £100,300 to £135,700; Senior Staff ML Engineer £119,000 to £161,000.