AI Research Engineer

Xaira Therapeutics
Location
South San Francisco, CA
Job Type
Full-time
Posted
June 2, 2026
Views
5
Salary Range
$190k - $280k USD

Job Description

Xaira is an AI-driven biotech developing generative AI models to design protein and antibody therapeutics, plus foundation models for biology and disease. Xaira is headquartered in the San Francisco Bay Area, Seattle, and London.

About the Role

We are seeking an experienced research engineer to join our team. As a critical member of our interdisciplinary group, you will collaborate closely with AI scientists, engineers, and drug discovery experts to develop and deploy AI models that accelerate the identification and development of novel therapeutics. This role offers the opportunity to apply cutting-edge AI techniques in production settings to address pressing challenges in healthcare and contribute to improving human health globally.

We are particularly interested in candidates who have demonstrated experience building and delivering machine learning systems in industry environments, where rigor, scalability, and cross-functional collaboration are essential. The ideal candidate has experience translating research ideas into robust, production-ready solutions that drive measurable impact. The role is open to the following locations: San Francisco Bay Area, Seattle.

Qualifications

  • Bachelor's degree in Computer Science, Engineering, or related fields; advanced degree preferred.
  • Minimum of five years of industry experience in AI, machine learning, or related roles, with a track record of implementing, scaling, and deploying AI models in production environments.
  • Expertise with modern deep learning toolchains and experience with large scale model training.
  • Strong understanding of deep learning fundamentals.
  • Excellent problem-solving skills, with a keen eye for detail and a passion for tackling complex challenges in the life sciences.
  • Effective communication and collaboration abilities, with the capacity to work effectively in a fast-paced, multidisciplinary team environment.
  • Publication track record at conferences such as NeurIPS, ICML, or ICLR is a plus, though demonstrated industry impact is prioritized.

Compensation: The base pay range for this position is expected to be $190,000 - $280,000 annually; the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience. The package also includes bonus and equity.

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Frequently Asked Questions

Where is the job located, and what is the work-mode policy?
The position is based in South San Francisco, CA, with the role open to the San Francisco Bay Area and Seattle. The text does not specify whether the work-mode policy is remote, hybrid, or on-site.
What qualifications and experience are required for this role?
You need a Bachelor's degree in Computer Science, Engineering, or a related field (advanced degree preferred) and at least five years of industry experience in AI or machine learning. You must also have experience implementing, scaling, and deploying AI models in production, plus expertise in deep learning toolchains.
What are the primary responsibilities of the AI Research Engineer?
You will collaborate with AI scientists, engineers, and drug discovery experts to develop and deploy AI models that accelerate the identification of novel therapeutics. You will translate research ideas into robust, production-ready solutions.
What is the compensation range for this position?
The expected annual base pay range is $190,000 to $280,000. The compensation package also includes a bonus and equity.
Who will I be working with in this role?
You will join an interdisciplinary team, collaborating closely with AI scientists, engineers, and drug discovery experts.

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Job Information

Source: manual
AI Relevance: 92/100 (Highly relevant)
Remote Type: onsite
Experience: Senior
Allowed Locations: San Francisco Bay Area, CA; Seattle, WA
Skills & Tags:
research engineer machine learning deep learning MLOps large-scale training production ML AI drug discovery life sciences

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