Xaira Therapeutics
Software Engineer, ML Platform
Seattle, Washington · Senior
Stay score
odds of building a lasting career here
Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.
Lottery odds assume a STEM candidate.
Personalize to your clock →H-1B wage level
the lottery is wage-weighted — each level is one more entry
$20,118 more — $160,118 — moves this role to Level III and 3 lottery entries. That figure is inside the range the employer already advertised.
Based on the DOL prevailing wage for this occupation and worksite, a base salary of $160,118 would place this position at wage Level III. That figure is within the posted range, and I'd like to target it. This role classifies under "Data Scientists" for prevailing-wage purposes.
DOL prevailing wage, 2026-27 wage year · Data Scientists (15-2051) · Seattle-Tacoma-Bellevue, WA. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.
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from this employer's Department of Labor filings
Files H-1B transfers
Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.
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About the role
- This role spans a range of problems and skillsets, ranging from MLOps of cutting-edge GPU clusters, to backend engineering of control plane APIs.
- You'll get to go in the lab, and for our ideal candidate, this should be a perk, not a chore!
- The base pay range for this position is expected to be $140,000 - $215,000 annually; however, the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.
Responsibilities
- Develop and improve our model training system, responsible for dispatching distributed training jobs to clusters across multiple clouds.
- 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.
- 5+ years of industry experience building and deploying ML systems in production environments
- 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.
Requirements
- Experience with infrastructure/ops tools such as Terraform, Ansible.
- Experience with the infrastructure needs of large-scale model training.
- Prior experience with biology is not required - we will teach what you need to know.
Nice to have
- Preferred Skills and Qualifications
Compensation
- We offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers.
- We offer a competitive package that includes base salary, bonus, and equity.
- The base pay range for this position is expected to be $140,000 - $215,000 annually; however, the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.
Benefits
- Degree in Computer Science, Machine Learning, Computational Biology, or a related field.
- Experience with deep learning frameworks such as Torch, Jax.
- Solid understanding of machine learning
- We offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers.
- A Summary of Benefits is available for all applicants.
Company info
- About the RoleWe 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.
This listing is sourced directly from Xaira Therapeutics's careers page and normalized into a canonical job model.