Senior Machine Learning Engineer

Our Mission

To restore cell health and resilience through cellular rejuvenation programming to reverse disease, injury, and the disabilities that can occur throughout life.

For more information, see our website at altoslabs.com.

Diversity at Altos

We believe that diverse perspectives are foundational to scientific innovation and inquiry. 

We are building a company where exceptional scientists and industry leaders from around the world work side by side to advance a shared mission. 

Our intentional focus is on Belonging, so that all employees know that they are valued for their unique perspectives. 

At Altos, we are all accountable for sustaining a diverse and inclusive environment.

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;
• Deploy & optimize new statistical and machine learning-based methods for analyzing biological data to produce biological insights about cell health and rejuvenation;
• Partner with world-class ML scientists & 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.

Who You Are

• Proven track record leveraging machine learning to solve real-world problems;
• Experience deploying data, training, optimization, and inference pipelines at scale in local or cloud-based distributed execution frameworks such as Ray, SLURM, or Kubernetes;
• Experience training and fine-tuning large language models;
• Experience in deploying and managing computational infrastructure for deep learning at scale, 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;
• Experience in the application of machine learning methods to biological data;
• Experience in computational approaches to drug discovery;
• Proven track record in open-source software development, e.g., demonstrated by high-impact GitHub repository;
• Proven track record of high-caliber scientific work, e.g., demonstrated through publications in peer-reviewed scientific journals.

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.

The salary range for this position is $212,500