Job description

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 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 What You Will Do GPUs go brrr. Identify bottlenecks, streamline network chatter, write kernels, and make the hardware fly. Experiment and Scale. Help unlock bigger models, longer training horizons, larger datasets, and weirder training dynamics. Implement the architecture. New architecture elements mix biological intuition with thinking in tensors. Translate molecules to matrices, and do it in a way that’s maintainable and clean to read. Make some drugs. Drug design campaigns involve heavy inference workloads and the inference harness is where molecule designer needs meet ML implementation skill. Build the tools that we use to make drugs. 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 - $305,000 annually with a total cash compensation up to $235,000 - $358,500; 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.

Requirements

Must-haves

GPUs go brrr. Identify bottlenecks, streamline network chatter, write kernels, and make the hardware fly.
Experiment and Scale. Help unlock bigger models, longer training horizons, larger datasets, and weirder training dynamics.
Implement the architecture. New architecture elements mix biological intuition with thinking in tensors. Translate molecules to matrices, and do it in a way that’s maintainable and clean to read.
Make some drugs. Drug design campaigns involve heavy inference workloads and the inference harness is where molecule designer needs meet ML implementation skill. Build the tools that we use to make drugs.
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.
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!

Nice-to-haves

Bachelor's degree in Computer Science, Engineering, or related fields; advanced degree preferred
Publication track record at conferences such as NeurIPS, ICML, or ICLR is a plus, though demonstrated industry impact is prioritized

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learninggoml

Platform: greenhouse
Effort: quick