Staff Machine Learning Engineer

What You Will Contribute To Altos

Altos Labs is seeking a Staff Machine Learning Engineer who can accelerate and optimize our progress in developing foundation models for biology. This role is integral to our Computational Systems Modeling & Scaling team, working in a team of experienced ML and infrastructure engineers to deliver compelling internal frameworks, services, and expertise. It will involve close collaboration with computational scientists from a diverse range of disciplines, including molecular modeling, computational biology, discrete simulation, machine learning, and artificial intelligence.

Responsibilities:

• Designing, building, and evaluating large-scale machine learning systems including data transformation pipelines, feature stores, distributed training, architecture optimization, model management & serving, etc.
• Motivated to build, deploy, and manage systems to accelerate large-scale machine learning workflows in an integrated, usable framework
• Interested in understanding user needs across a wide range of scientific disciplines, and communicating with users to build systems that they can use productively
• Demonstrated software engineering skills in developing reliable, scalable, performant systems in a cloud environment
• Champion maintainable, scalable, and reusable software engineering techniques and acts as an ambassador to promote effective tools and practices to the research community.
• Mentor software engineers and computational scientists, evangelizing best practices around development tools, CI/CD, and other methods to improve code quality and efficiency.

Who You Are

Minimum Qualifications

• M.S. or Ph.D. in Computer Science, or related quantitative field, or equivalent technical experience
• 8+ years software development experience
• Extensive experience with large scale machine learning tools and infrastructure.
• Experience applying software engineering practices in a scientific environment, or another environment with similar characteristics
• Excited to design, implement, and evangelize technical and cultural standards across scientific and technical functions.
• Proven track record of delivering high quality software.
• Skilled at working effectively with cross-functional teams, including research and engineering organizations.
• Excellent written and verbal communication skills.

Preferred Qualifications

• Familiarity with biological data formats, concepts, and computational models is a plus