Altos Labs
Machine Learning Engineer, Computer Vision
Altos Labs, San Diego, California, United States, 92189
Overview
Machine Learning Engineer, Computer Vision — Altos Labs Join to apply for the Machine Learning Engineer, Computer Vision role at Altos Labs. Our Mission & Values
Our mission is to restore cell health and resilience through cell rejuvenation to reverse disease, injury, and the disabilities that can occur throughout life. Our Single Altos Value: Everyone Owns Achieving Our Inspiring Mission. Diversity & Belonging
We believe that diverse perspectives are foundational to scientific innovation and inquiry. At Altos, exceptional scientists and industry leaders from around the world work together to advance a shared mission. Belonging is a focus so that all employees are valued for their unique perspectives. We are accountable for sustaining a diverse and inclusive environment. What You Will Contribute To Altos
At Altos Labs, our mission to unravel the mysteries of cell rejuvenation and human health hinges on groundbreaking quantitative solutions. The role of a Machine Learning Engineer is to architect high-performance, scalable systems that translate complex biomedical imagery and multi-omics data into actionable insights. The role enables and accelerates the mission by pioneering state-of-the-art computer vision and machine learning applications. The best candidate bridges cutting-edge scientific discovery with robust, accessible computational tools. Contributions impact multiple scales of biomedical data—from Electron/Light Microscopy and Digital Histology/Pathology to in vivo functional analysis. You will collaborate with our ML Ops team to ensure models are powerful, trainable, discoverable, interpretable, and accessible across diverse research groups. Responsibilities
Pioneer Model Development & Optimization: Evaluate and re-engineer state-of-the-art AI models across imaging domains, including de novo protein design, structure identification, and dynamics in single-particle CryoEM. Integrate light microscopy and multi-omics data for cross-domain mapping of in situ and in vivo data. Architect Scalable Distributed Systems: Design, develop, and implement reliable, performant, and scalable distributed systems within a cloud environment. Optimize Data Pipelining for Exascale Training: Develop efficient data loading strategies and robust performance tracking for training large-scale models, orchestrating distributed training across compute nodes. Forge Integrated Analysis Pipelines: Engineer and manage complex multi-modal analysis pipelines to enable advanced scientific and ML workflows. Bridge the Technical and Scientific Divide: Translate complex technical concepts between experimental scientists, algorithm developers, and deployment engineers to enable successful project execution. Drive Technical & Cultural Excellence: Champion technical and cultural standards across scientific and engineering functions, ensuring code quality, collaboration, and continuous innovation. Who You Are
Minimum Qualifications
BS/MS in Computer Science, Biomedical Engineering, or a closely related quantitative field. 2-5 years of hands-on experience in relevant industry and/or academic settings with tangible results. Mastery of core programming languages for large-scale data management and ML, including Python and C++, with deep experience in PyTorch/TensorFlow and PyTorch Lightning. Demonstrable expertise in ML at scale, with practical experience in Large Language Models, self-supervised/contrastive/representation learning for computer vision, and multi-modal data integration. Proven ability to apply rigorous software engineering practices in a scientific or high-stakes environment. Strong track record of hands-on technical leadership and significant scientific contributions, evidenced by publications or conference presentations. Enthusiasm to design, implement, and champion technical and cultural standards that elevate the scientific and technical ecosystem. Preferred Qualifications
Experience with bioinformatics data processing and analysis. Expertise in multi-source data integration and solving challenges across disparate datasets. Practical experience with cloud computing platforms and containerization for scalable deployments. Knowledge of genetics and/or human genetics. Salary
The salary ranges vary by location: San Francisco Bay Area, CA — Machine Learning Engineer I: $153,000 - $207,000; Machine Learning Engineer II: $178,500 - $241,500 San Diego, CA — Machine Learning Engineer I: $150,450 - $203,550; Machine Learning Engineer II: $170,000 - $230,000 Exact compensation may vary based on skills, experience, and location. Privacy & Equal Opportunity
For UK applicants: privacy notice considerations apply. Altos Labs is an equal employment opportunity employer. We value collaboration and scientific excellence. We believe diverse perspectives and a culture of belonging are foundational to scientific innovation. Altos Labs prohibits unlawful discrimination and harassment and provides equal employment opportunities to all employees and applicants without regard to race, color, religion, age, sex, national origin, disability, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by law. Altos Labs requires all employees to be fully vaccinated against COVID-19, subject to legally required exemptions. This content does not constitute a contract and is informational only. Note: Altos Labs will not ask you to download a messaging app for an interview or to outlay money to begin employment. If you encounter suspicious contact claiming to be with Altos, please verify through official channels. Seniority level
Mid-Senior level Employment type
Full-time Job function
Engineering and Information Technology Industries: Biotechnology Research, Pharmaceutical Manufacturing, Information and Internet
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Machine Learning Engineer, Computer Vision — Altos Labs Join to apply for the Machine Learning Engineer, Computer Vision role at Altos Labs. Our Mission & Values
Our mission is to restore cell health and resilience through cell rejuvenation to reverse disease, injury, and the disabilities that can occur throughout life. Our Single Altos Value: Everyone Owns Achieving Our Inspiring Mission. Diversity & Belonging
We believe that diverse perspectives are foundational to scientific innovation and inquiry. At Altos, exceptional scientists and industry leaders from around the world work together to advance a shared mission. Belonging is a focus so that all employees are valued for their unique perspectives. We are accountable for sustaining a diverse and inclusive environment. What You Will Contribute To Altos
At Altos Labs, our mission to unravel the mysteries of cell rejuvenation and human health hinges on groundbreaking quantitative solutions. The role of a Machine Learning Engineer is to architect high-performance, scalable systems that translate complex biomedical imagery and multi-omics data into actionable insights. The role enables and accelerates the mission by pioneering state-of-the-art computer vision and machine learning applications. The best candidate bridges cutting-edge scientific discovery with robust, accessible computational tools. Contributions impact multiple scales of biomedical data—from Electron/Light Microscopy and Digital Histology/Pathology to in vivo functional analysis. You will collaborate with our ML Ops team to ensure models are powerful, trainable, discoverable, interpretable, and accessible across diverse research groups. Responsibilities
Pioneer Model Development & Optimization: Evaluate and re-engineer state-of-the-art AI models across imaging domains, including de novo protein design, structure identification, and dynamics in single-particle CryoEM. Integrate light microscopy and multi-omics data for cross-domain mapping of in situ and in vivo data. Architect Scalable Distributed Systems: Design, develop, and implement reliable, performant, and scalable distributed systems within a cloud environment. Optimize Data Pipelining for Exascale Training: Develop efficient data loading strategies and robust performance tracking for training large-scale models, orchestrating distributed training across compute nodes. Forge Integrated Analysis Pipelines: Engineer and manage complex multi-modal analysis pipelines to enable advanced scientific and ML workflows. Bridge the Technical and Scientific Divide: Translate complex technical concepts between experimental scientists, algorithm developers, and deployment engineers to enable successful project execution. Drive Technical & Cultural Excellence: Champion technical and cultural standards across scientific and engineering functions, ensuring code quality, collaboration, and continuous innovation. Who You Are
Minimum Qualifications
BS/MS in Computer Science, Biomedical Engineering, or a closely related quantitative field. 2-5 years of hands-on experience in relevant industry and/or academic settings with tangible results. Mastery of core programming languages for large-scale data management and ML, including Python and C++, with deep experience in PyTorch/TensorFlow and PyTorch Lightning. Demonstrable expertise in ML at scale, with practical experience in Large Language Models, self-supervised/contrastive/representation learning for computer vision, and multi-modal data integration. Proven ability to apply rigorous software engineering practices in a scientific or high-stakes environment. Strong track record of hands-on technical leadership and significant scientific contributions, evidenced by publications or conference presentations. Enthusiasm to design, implement, and champion technical and cultural standards that elevate the scientific and technical ecosystem. Preferred Qualifications
Experience with bioinformatics data processing and analysis. Expertise in multi-source data integration and solving challenges across disparate datasets. Practical experience with cloud computing platforms and containerization for scalable deployments. Knowledge of genetics and/or human genetics. Salary
The salary ranges vary by location: San Francisco Bay Area, CA — Machine Learning Engineer I: $153,000 - $207,000; Machine Learning Engineer II: $178,500 - $241,500 San Diego, CA — Machine Learning Engineer I: $150,450 - $203,550; Machine Learning Engineer II: $170,000 - $230,000 Exact compensation may vary based on skills, experience, and location. Privacy & Equal Opportunity
For UK applicants: privacy notice considerations apply. Altos Labs is an equal employment opportunity employer. We value collaboration and scientific excellence. We believe diverse perspectives and a culture of belonging are foundational to scientific innovation. Altos Labs prohibits unlawful discrimination and harassment and provides equal employment opportunities to all employees and applicants without regard to race, color, religion, age, sex, national origin, disability, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by law. Altos Labs requires all employees to be fully vaccinated against COVID-19, subject to legally required exemptions. This content does not constitute a contract and is informational only. Note: Altos Labs will not ask you to download a messaging app for an interview or to outlay money to begin employment. If you encounter suspicious contact claiming to be with Altos, please verify through official channels. Seniority level
Mid-Senior level Employment type
Full-time Job function
Engineering and Information Technology Industries: Biotechnology Research, Pharmaceutical Manufacturing, Information and Internet
#J-18808-Ljbffr