Senior/ Staff AI Research Engineer

Xaira Therapeutics

$205K — $275K *
Pharmaceuticals & Biotech
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Computer Science, Engineering, or related fields; advanced degree preferred
  • Minimum of five years of industry experience in AI or machine learning, focusing on implementation and deployment of AI models
  • Expertise with modern deep learning frameworks and large-scale model training
  • Strong grasp of deep learning fundamentals
  • Excellent problem-solving skills with attention to detail
  • Strong communication and collaboration abilities in multidisciplinary environments
  • A publication track record at conferences like NeurIPS, ICML, or ICLR is a plus, although industry impact is prioritized

Responsibilities

  • Collaborate with AI scientists, engineers, and drug discovery experts to develop AI models
  • Deploy AI models aimed at accelerating the identification of novel therapeutics
  • Translate research concepts into production-ready AI solutions
  • Implement and scale AI systems in industry environments
  • Tackle complex challenges to improve human health through innovative approaches
  • Engage in cross-functional teamwork to ensure project success
  • Leverage cutting-edge AI techniques to drive measurable impact in healthcare

Benefits

  • Flexible work environment
  • Friendly workplace culture
  • Opportunities for career development
  • Comprehensive benefits package covering various aspects of employee well-being
Full Job Description
About the RoleWe 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
  • If you are a motivated individual with a passion for applying AI to advance drug discovery and improve human health, we encourage you to apply!


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 to $275,000 annually; however, the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.

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