Remote hybrid: Persons in these roles are expected to spend part of their time on-site in our Seattle offices but may occasionally work remotely. On-site requirements vary based on position and team. Fully remote roles may be considered for exceptional candidates. 

Who you are:

You have Ph.D.-level expertise in machine learning and physically-based numerical modeling.  You yearn to rise to the challenge of using ML to make better climate models as part of a world-leading AI2 research team that works closely with top U.S. climate modeling institutions.  You are a thought leader and a team player who delivers cutting-edge research and well-crafted code that breaks barriers.

Your next challenge:

AI2’s Climate Modeling team is an international pioneer in using machine learning (ML) methodologies to improve current climate models.  We seek a Research Scientist to use novel ML approaches to enable coarse-grid climate models to better emulate the weather and climate of ultra-fine grid reference simulations. You will join a tight-knit team of scientists and software engineers collaborating with external climate modeling groups.  AI2 is a non-profit research institute in beautiful, vibrant Seattle focused on developing AI for the public good.  Its 200-person staff research areas of AI such as natural language processing, vision and robotics, and environmental AI.  AI2 is committed to providing an excellent work environment and hiring a diverse workforce.  More detail about the AI2 mission and values is below.

In AI2’s mission-driven environment you’ll have the opportunity to:

  • Collaboratively design and deploy the next generation of our ML system that makes computationally efficient numerical models of the global atmosphere much more accurate for simulating past and future climates.
  • Help create an open-source product that the climate modeling community can really use.
  • Experiment with novel ML methodologies in a rapidly evolving field of study.
  • Disseminate new methods and findings in conferences and scientific journals.
  • Work with and learn from team members in the Climate Modeling group and across AI2.
  • Mentor graduate student interns 

What you’ll need:

  • You must have substantial experience building and deploying an ML application in a practical or academic research setting and be fluent in Python and collaborative coding practices.  
  • You must have a Ph. D. in computer or computational science, atmospheric science or a related geophysical science, or applied mathematics/statistics, with at least one first-authored publication making extensive use of ML. Formal graduate-level ML coursework is a plus.
  • You should have formal training and/or practical experience with physically-based numerical modeling.  Experience in atmospheric model development is a plus.
  • You should be creative, curious, collaborative, a deep thinker, a careful coder, and an excellent communicator.
  • A past professional or post-doctoral position using your machine learning skills is a plus.
  • Exceptionally qualified candidates more than four years post-Ph.D. may be eligible for a senior-level research scientist position.

Required Submissions:

  • CV
  • Example of ML-based research (Link or article)
  • References upon request

Application Deadline: November 15th, 2022

AI2: a great place to work:

The Allen Institute for Artificial Intelligence is a non-profit research institute in Seattle founded by Paul Allen. AI2 contributes to humanity through high-impact research in artificial intelligence. 

We also aim to contribute to humanity through our treatment of each member of the AI2 Team: 

  • We are a learning organization – because everything AI2 does is ground-breaking, we are learning every day. Similarly, through weekly AI2 Academy lectures, a wide variety of world-class AI experts as guest speakers, and our commitment to your personal on-going education, AI2 is a place where you will have opportunities to continue learning alongside your coworkers. 
  • We value diversity - We seek to hire, support, and promote people from all genders, ethnicities, and all levels of experience regardless of age. We particularly encourage applications from women, non-binary individuals, people of color, members of the LGBTQA+ community, and people with disabilities of any kind. 
  • We value inclusion - We understand the value that people's individual experiences and perspectives can bring to an organization, and we are building a culture in which all voices are heard, respected and considered.
  • We emphasize a healthy work/life balance – we believe our team members are happiest and most productive when their work/life balance is optimized. While we value powerful research results which drive our mission forward, we also value dinner with family, weekend time, and vacation time. We offer generous paid vacation and sick leave as well as family leave.
  • We are collaborative and transparent – we consider ourselves a team, all moving with a common purpose. We are quick to cheer our successes, and even quicker to share and jointly problem solve our failures.
  • We are in Seattle – and our office is on the water! We have mountains, we have lakes, we have four seasons, we bike to work, we have a vibrant theater scene, and we have so much else. We even have kayaks for you to paddle right outside our front door. We welcome interest from applicants from outside of the United States.
  • We are friendly– chances are you will like every one of the 200+ (and growing) people who work here. We do. 

AI2 is proud to be an Equal Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. 

If you need assistance or an accommodation due to a disability, you may contact us at  or you may call us at 206-548-5600.


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