Machine Learning Engineer

Job Description

Altos Labs is seeking a Machine Learning Engineer to contribute to building high-performance, scalable, quantitative solutions for biomedical image analysis and integration with multi-Omics data. The engineer will work with a team focused on multiple scales of data, from Electron/Light Microscopy to Digital Histology and Pathology, up to functional analysis In Vivo. The role involves leveraging state-of-the-art computer vision and machine learning techniques, and collaborating with MLOps to ensure models are easily trainable, findable, interpretable, and accessible across diverse research groups.Responsibilities include:

• Evaluating and retraining AI models across various imaging modalities.
• Developing reliable, scalable, and performant distributed systems in a cloud environment.
• Creating efficient data loading strategies and performance tracking for large-scale model training.
• Building, deploying, and managing multi-modal analysis pipelines and machine learning workflows.
• Understanding scientists' needs and bridging the communication gap between experimental scientists, algorithm developers, and software deployers.

Minimum qualifications include:

• BS/MS in Computer Science/Biomedical Engineering or a related quantitative field.
• 2-5 years of relevant industry and/or academic experience.
• Experience with programming languages such as Python, C++, Pytorch/Tensorflow, Pytorch Lightning.
• Experience with Machine Learning at scale, including Large Language Models and Self-Supervised/Contrastive/Representation Learning for Computer Vision applications and multi modal integration.
• Experience applying software engineering practices in a scientific environment.
• A track record of technical leadership and scientific contributions.

Altos Labs offers:

• A culture of collaboration and scientific excellence.
• An inclusive and belonging environment.