Senior ML Platform Engineer for Distributed GPU Training

Xairatherapeutics; Seattle (WA); On-site; USD 205,000 - 325,000; Full time

Benefits offered by this job

Equity

Bonus

Job summary

Xaira Therapeutics seeks a Senior Software Engineer to design, build, and deploy the AI infrastructure powering our research teams. You will enable thousands of GPUs for training and inference of biological foundation models across multi-cloud clusters.

Ideal candidates have 5+ years of experience deploying ML systems, strong Python skills, and a track record of technical leadership. The role emphasizes backend tooling and scalable pipelines in a collaborative, interdisciplinary environment.

Qualifications

• 5+ years building and deploying ML systems in production.
• Experience leading technical projects and cross-functional execution.
• Strong Python programming skills.
• Experience with infrastructure/ops tools such as Terraform and Ansible.
• Experience with deep learning frameworks such as Torch and Jax.

Responsibilities

• Develop and improve our model training system, dispatching distributed training jobs to clusters across multiple clouds.
• Deploy storage subsystems to improve dataset management and throughput for training datasets.
• Build evaluation infrastructure for easy execution and tracking.
• Build base tooling to integrate model training with telemetry, experiment tracking, and checkpointing.
• Collaborate with AI Scientists and other engineers; knowledge of biology not required to start, but possible lab exposure is a perk.

Skills

Python programming

ML systems production

Project leadership

Slurm/Kubernetes approach

Problem solving

Collaboration

Education

Degree in Computer Science / ML / Computational Biology or related field

Tools

Terraform

Ansible

Torch

Jax

Job description

Xaira Therapeutics seeks a Senior Software Engineer to design, build, and deploy the AI infrastructure powering our research teams. You will enable thousands of GPUs for training and inference of biological foundation models across multi-cloud clusters.

Ideal candidates have 5+ years of experience deploying ML systems, strong Python skills, and a track record of technical leadership. The role emphasizes backend tooling and scalable pipelines in a collaborative, interdisciplinary environment.