AI Scientist, Computational Protein Design

Xaira Therapeutics

$120K — $240K *
Pharmaceuticals & Biotech
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field
  • 3+ years post-PhD experience in an industrial setting or equivalent academic post-doctoral experience
  • Proven track record of AI innovation with publications in leading AI/ML journals
  • Expertise in deep learning development and implementation
  • Proficient in PyTorch and large model training/inference on GPUs
  • Scientific curiosity with a collaborative mindset for interdisciplinary projects
  • Experience bridging AI with biological applications.

Responsibilities

  • Drive new AI projects that enhance state-of-the-art models for biology
  • Collaborate with interdisciplinary teams in drug discovery and clinical development
  • Research and innovate in methods for deep learning applications
  • Engage in large-scale distributed training and inference
  • Communicate results and research effectively to peers and public audiences
  • Participate in and contribute to open-source initiatives
  • Mentor and support junior team members in AI applications.

Benefits

  • Open and flexible work environment
  • Friendly company culture
  • Opportunities for long-term career development
  • Inclusive of diverse backgrounds and experiences
  • Summary of benefits provided for all applicants.
Full Job Description
About the Role

As an AI Scientist, you will have prior experience in developing and implementing new deep learning methods while upholding a track record of AI Innovation demonstrated through publications in Artificial Intelligence/Machine Learning or projects applying them to interdisciplinary fields. You will be a crucial member of our core AI team, comprising highly creative and talented peers who are all experts in developing state of the art AI models. With your team, you will initiate and drive new projects that advance the SOTA AI models for biology impacting drug discovery and clinical development. You will also have the chance to work closely with interdisciplinary experts with world-class biology, drug discovery, and clinical expertise.

We welcome candidates with diverse backgrounds and experiences. Whether you are an entry-level candidate eager to learn and grow, a mid-level professional seeking new challenges, or a seasoned expert looking to make a significant impact, we encourage you to apply.

Qualifications
  • Track record of AI Innovation demonstrated through publications in Artificial Intelligence/Machine Learning or projects applying them to interdisciplinary fields
  • Experienced in developing and implementing new deep learning methods
  • Experienced in PyTorch, training and inference of large models on GPUs
  • Scientifically curious with an interest to work on interdisciplinary teams
  • PhD in Computer Science/Artificial Intelligence/ Machine Learning or related technical fields
  • 3+ years of work experience post-PhD in an industrial setting or equivalent academic post-doctoral experience
  • Peer reviewed published research in developing AI methods (example in ICLR, NeurIPS, ICML, Nature, Science, Cell etc.)
  • Experience in working at the interface of AI and Biology
  • Experience working on large scale distributed training and inference
  • Experience communicating research for public audiences of peers
  • Participation in the open-source community


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 $120,000 - $240,000 annually; however, the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.

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