Principal Infrastructure Engineer (Machine Learning)
Principal Infrastructure Engineer (Machine Learning)
Location
San Fransisco, United States
Business Sector
Biotechnology
Contact email
Job ref
24823
Published
1 day ago
We are seeking a Principal Infrastructure Engineer (Machine Learning) to lead the development of cutting-edge AI infrastructure to power generative modeling of molecular systems for a scaling BioTech company.
Key Responsibilities:
Lead the design and implementation of scalable infrastructure for distributed ML training, inference, and evaluation across multi-cloud and multi-cluster environments.
Optimize ML workflows for speed, efficiency, and resource utilization, including low-level GPU tuning and performance engineering.
Build and maintain core MLOps tools, frameworks, and training pipelines that support the latest in generative modeling.
Define the long-term architecture and technical vision for the machine learning platform, driving innovation and scalability.
Qualifications and Experience:
Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.
7+ years of experience in software or machine learning engineering, with a strong focus on ML infrastructure and distributed systems.
Deep understanding of distributed systems and experience engineering robust ML infrastructure from the ground up.
Proficiency in designing scalable, production-grade ML pipelines that span multiple clouds and clusters.
Can this role be interesting for you or anyone you know? If so, please send your CV and contact information to d.sonneveld@panda-int.com, and we will be in touch for a conversation.
Position: Principal Infrastructure Engineer (Machine Learning) Location: South San Francisco Contract: Permanent Start Date: By agreement