AI Research Engineer

Employment Type: [Not Specified] Location Type: [Not Specified] Salary: [Not Specified]

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.

Position Overview

We are seeking an experienced AI Research Engineer to join our team and lead some of our efforts in building the AI powered future of drug discovery. As a senior member of our interdisciplinary group, you will collaborate closely with AI scientists, other engineers, and drug discovery experts to help develop AI models to accelerate the identification and development of novel therapeutics. This role offers a unique opportunity to leverage cutting-edge AI techniques to address pressing challenges in healthcare and contribute to improving human health globally.

Key Responsibilities

• Drive the development of state-of-the-art AI models for drug discovery tasks, leveraging deep learning frameworks.
• Scale distributed training of large AI models on GPUs.
• Profile and optimize AI models in training and inference contexts.
• Stay abreast of the latest advancements in AI, machine learning and proactively identify opportunities for innovation and improvement.
• Contribute to technical documentation, reports, and presentations to communicate findings, methodologies, and insights clearly and effectively.
• Provide deep technical leadership on the development and optimization of core AI models that power our drug discovery efforts.

Minimum Qualifications

• Bachelor's degree in Computer Science, Engineering, or related fields.
• 7+ years of industry experience in AI, machine learning, or related roles, with a track record of successfully implementing and deploying AI models in production environments.
• Proficiency in programming languages such as Python, C++ and deep expertise with frameworks such as PyTorch/Jax.
• Strong understanding of deep learning fundamentals, including neural network architectures, optimization techniques, and evaluation metrics.
• Experience in distributed training and inference of large scale AI models on thousands of GPUs using DDP, FSDP etc.
• Experience with performance optimization of large scale AI models.
• Effective communication and collaboration abilities, with the capacity to work effectively in a fast-paced, multidisciplinary team environment.
• Experience solving complex problems and comparing alternative solutions, tradeoffs, and diverse points of view to determine a path forward.

Preferred Qualifications

• Publication track record at conferences such as NeurIPS, ICML, ICLR, etc.
• Experience working and communicating cross-functionally on an interdisciplinary team.
• Experience with different GPU architectures, cloud environments and investigating tradeoffs.
• Experience with low-level hardware optimization and with custom CUDA kernels.
• Contributions to open source projects.

Benefits

• Opportunity to make a meaningful impact by contributing to groundbreaking research at the intersection of AI and healthcare.
• Competitive compensation package, including salary, bonuses, and benefits.
• Professional development opportunities, including access to conferences, workshops, and training programs.
• A collaborative and inclusive work culture that values diversity, creativity, and continuous learning.
• Chance to work with and develop cutting-edge technologies and contribute to projects with significant societal benefit.

If you are a motivated individual with a passion for applying AI to advance drug discovery, we encourage you to apply.