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Xaira Therapeutics

Senior Software Engineer, ML Platform

Xaira Therapeutics is hiring a Senior Software Engineer, ML Platform in Seattle, United States. It pays $205k-$275k a year and Level rates it ; you can apply on Xaira Therapeutics.

Level's read on this job

  • On Level's scale, this software engineer role is Builds AI ●●●●: the job is building AI systems.
  • Pay on this posting starts 22% higher than the typical software engineer posting on Level.
  • The posting mentions JAX, Python and Kubernetes among its tools and skills.
  • Level classes it as a senior role.
  • Xaira Therapeutics has 30 other open roles on Level.

AI in this role

Build and scale AI infrastructure, GPU clusters, and model training systems for biological foundation models.

jaxpythonkubernetesterraformslurm
ml-opsmlopsdistributed-traininginfrastructuregpu-cluster-management

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 Senior 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 to know.  You’ll get to go in the lab, and for our ideal candidate, this should be a perk, not a chore!

Preferred Skills and Qualifications

  • Degree in Computer Science, Machine Learning, Computational Biology, or a related field.
  • 5+ years of industry experience building and deploying ML systems in production environments
  • Experience leading technical projects and driving cross-functional execution.
  • Strong programming skills in Python.
  • Experience with infrastructure/ops tools such as Terraform, Ansible.
  • Experience with deep learning frameworks such as Torch, Jax.
  • Solid understanding of machine learning
  • Experience with the infrastructure needs of large-scale model training.
  • Strong problem-solving skills and ability to work in a collaborative, multidisciplinary environment.

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. A Summary of Benefits is available for all applicants. We offer a competitive package that includes base salary, bonus, and equity. The base pay range for this position is expected to be $205,000 - $275,000 annually with a total cash compensation up to $235,000 - $325,000; however, the compensation offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.

Xaira Therapeutics an equal-opportunity employer. We believe that our strength is in our differences. Our goal to build a diverse and inclusive team began on day one, and it will never end.

TO ALL RECRUITMENT AGENCIES: Xaira Therapeutics does not accept agency resumes. Please do not forward resumes to our jobs alias or employees. Xaira Therapeutics is not responsible for any fees related to unsolicited resumes.

How we rate this

Senior Software Engineer, ML Platform at Xaira Therapeutics rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

ML OpsMLOpsDistributed TrainingInfrastructureGPU Cluster ManagementJAXPythonKubernetes

Also common in software engineer jobs at this level

Pay

This job starts at
$205k
Typical software engineer job
$168k

This posting starts 22% above the typical software engineer job. See software engineer jobs

Questions you could be asked

  1. How do you monitor a model once it's live, and how do you know it needs retraining?
  2. Tell me about a project where mlops was part of your work. What did you do?
  3. Tell me about a project where distributed training was part of your work. What did you do?
  4. Tell me about a project where infrastructure was part of your work. What did you do?
  5. Tell me about a project where gpu cluster management was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: ML Ops, MLOps, Distributed Training, Infrastructure, and GPU Cluster Management. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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