Xaira Therapeutics
Biotech
SoftwareEngineer,MLPlatform
Neural analysis suggests this role is
optimal for Senior candidates.
“Software Engineer, ML Platform at Xaira Therapeutics. Skills: ML Platform, GPU clusters, Foundation models. Develop model training system. Improve model training system”
Industry & Context.
Problem-solving skills
What They're Looking For.
Must Have
5+ years industry experience, Programming skills in Python, Experience with infrastructure/ops tools, Experience with deep learning frameworks, Solid understanding of machine learning, Experience with infrastructure needs
Nice to Have
Degree in CS, ML, Computational Biology, Experience leading technical projects, Experience with Terraform, Experience with Ansible, Experience with Torch, Experience with Jax, Experience with slurm, Experience with kubernetes, Experience maximizing GPU bandwidth, Experience building API paved path
What You'll Do.
Develop model training system
Improve model training system
Dispatch distributed training jobs
Deploy storage subsystems
Improve dataset management
Build evaluation infrastructure
Enable easy execution
Integrate model training
Integrate experiment tracking
Integrate checkpointing
How You'll Work.
Team & Collaboration
AI Scientists; Other engineers
Full Job Description
About Xaira Therapeutics Xaira is an innovative biotech startup focused on leveraging AI to transform drug discovery and development. The company is leading the development of generative AI models to design protein and antibody therapeutics, enabling the creation of medicines against historically hard-to-drug molecular targets. It is also developing foundation models for biology and disease to enable better target elucidation and patient stratification. Collectively, these technologies aim to continually enable the identification of novel therapies and to improve success in drug development. Xaira is headquartered in the San Francisco Bay Area, Seattle, and London. About the Role We are seeking a Software Engineer to join our Platform team to design, build, and deploy the AI infrastructure that powers our world-class research team. In this role, you’ll collaborate closely with AI Scientists and other engineers to enable the effective use of thousands of GPUs for training and inferencing cutting-edge biological foundation models. This role spans a range of problems and skillsets, ranging from MLOps of cutting-edge GPU clusters, to backend engineering of control plane APIs. Our ideal candidate has an opinion about slurm or kubernetes for model training, cares about maximizing bandwidth from the storage subsystems to the GPU, and can build the API paved path for submitting training jobs that are able to dispatch to multiple clusters. What You Will Do Develop and improve our model training system, responsible for dispatching distributed training jobs to clusters across multiple clouds. Deploy storage subsystems that improve dataset management and throughput for training datasets. Build evaluation infrastructure that enables easy execution and tracking. Build base tooling for integrating model training with other internal infrastructure, such as telemetry, experiment tracking, and checkpointing. Prior experience with biology is not required - we will teach what you need
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