The Staff Platform Engineer will design, develop, and maintain the Altos cloud platform, supporting cloud infrastructure and scientific computing systems. Responsibilities include implementing technologies for deploying scientific applications, optimizing system performance, facilitating cloud technology adoption, and improving reliability through automation and testing.

As a Staff Machine Learning Engineer, you'll design and evaluate large-scale machine learning systems, manage workflows, and mentor other engineers. You'll collaborate with computational scientists to create user-friendly frameworks that enhance productivity across scientific disciplines.

Altos Labs invites individuals to join their talent community. The company is focused on enhancing cell health to reverse diseases and disability. The emphasis is on diversity and inclusion in fostering scientific innovation and collaboration. This position is an opportunity to submit your resume for consideration in future job openings.

As a Scientist in Machine Learning, you will develop generative AI models for biomedical image analysis and integrate multi-omics data. Responsibilities include building scalable machine learning workflows, collaborating to understand scientists' needs, and ensuring system reliability in a cloud environment.

The Data Scientist will generate insights and models from multi-omics datasets, build data pipelines for analysis, and collaborate with lab scientists to accelerate research efforts. Responsibilities include staying updated with new methodologies and embedding analyses in automated reports.

The Data Scientist will generate insights from multi-omics datasets, build data analysis pipelines, collaborate with lab scientists, and utilize advanced analytical methodologies. The role requires proficiency in programming and the ability to contribute to innovative projects in cell health and genomics.

As a Senior Scientist in In Vitro Pharmacology, you will lead the development of biophysical, biochemical, and cell-based assays for drug discovery and validation. You'll manage projects, collaborate with cross-functional teams, and contribute to understanding mechanisms of aging and rejuvenation biology.

The Machine Learning Engineer will develop and optimize machine learning models for biomedical applications, working within scientific teams to evaluate AI technologies, enhance model performance, and facilitate the integration of multi-Omics data. Key responsibilities include building scalable systems in cloud environments and managing analysis pipelines.

As a Hub Scientist in the Mass Spectrometry Innovation Hub, you will design and execute experimental methodologies while maintaining mass spectrometers and liquid chromatography instruments. Responsibilities include data analysis, document preparation, problem-solving with instrumentation, and collaboration with research teams to drive scientific discovery.

The Staff Machine Learning Engineer at Altos Labs will design and optimize large-scale machine learning systems, collaborating closely with computational scientists across various disciplines. Responsibilities include building data transformation pipelines, managing model serving, and mentoring software engineers while promoting effective software engineering practices.

Join Altos Labs' Talent Community by submitting your resume for future job opportunities. The company focuses on cell health and rejuvenation, fostering inclusivity and collaboration among diverse staff to drive innovation in scientific excellence.

The Scientist in Machine Learning will develop Generative AI models for integrating imaging and multi-omics data, create scalable distributed systems, and manage multi-modal analysis pipelines, while collaborating with scientists to meet diverse data needs.

The Computational Scientist will collaborate with a multidisciplinary team to develop computational and machine learning platforms using omics data, process sequencing data, establish analytical pipelines, and contribute to scientific initiatives.

The candidate will lead the development and application of AI and machine learning methods to analyze spatial omics and microscopy data related to biology, with a focus on tissue architecture and cell communication. Collaboration with experimental groups and contributions to publications and seminars are expected.