Altos Labs needs to translate complex biomedical imagery and multi-omics data into actionable insights by building high-performance, scalable systems for cell rejuvenation research.
Requirements
- Mastery of core programming languages critical for large-scale data management and machine learning, including Python, C++, and deep proficiency with frameworks like PyTorch/TensorFlow, and PyTorch Lightning.
- Demonstrable expertise in Machine Learning at scale, with practical experience in Large Language Models, Self-Supervised/Contrastive/Representation Learning for Computer Vision applications, and multi-modal data integration.
- Proven capability in applying rigorous software engineering practices within a scientific or similarly demanding, high-stakes environment.
- A strong, demonstrable track record of hands-on technical leadership and significant scientific contributions, as evidenced by publications or conference presentations.
- An innate enthusiasm to design, implement, and champion technical and cultural standards that elevate our entire scientific and technical ecosystem.
- Prior experience with bioinformatics data processing and analysis, showcasing a relevant domain understanding.
- Expertise in multi-source data integration, solving complex challenges in disparate datasets.
Responsibilities
- Pioneer Model Development & Optimization: The Machine Learning Engineer will be at the forefront, meticulously evaluating and re-engineering state-of-the-art AI models across the entire spectrum of imaging. This includes developing solutions for de novo protein design, structure identification, and dynamics in single-particle CryoEM, as well as integrating light microscopy and multi-omics data for cross-domain mapping of in situ and *in vivo
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- Architect Scalable Distributed Systems:
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- Leverage deep software engineering skills to design, develop, and implement reliable, performant, and inherently scalable distributed systems within a dynamic cloud environment.
- Optimize Data Pipelining for Exascale Training:
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- Take ownership of developing highly efficient data loading strategies and robust performance tracking mechanisms essential for training colossal models.
- Forge Integrated Analysis Pipelines:
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- Engineer, deploy, and meticulously manage complex multi-modal analysis pipelines that serve as the bedrock for scientific analysis and sophisticated machine learning workflows.
- Bridge the Technical and Scientific Divide:
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- Serve as the essential communication conduit, adeptly translating complex technical concepts between experimental scientists, advanced algorithm developers, and deployment engineers.
- Drive Technical & Cultural Excellence:
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- Proactive force in designing and championing technical and cultural standards across both scientific and engineering functions.
Other
- Everyone Owns Achieving Our Inspiring Mission.
- Our intentional focus is on Belonging, so that all employees know that they are valued for their unique perspectives.
- We are all accountable for sustaining a diverse and inclusive environment.
- Serve as the essential communication conduit, adeptly translating complex technical concepts between experimental scientists, advanced algorithm developers, and deployment engineers.
- Proactive force in designing and championing technical and cultural standards across both scientific and engineering functions.
