Machine Learning Scientist - Axiom Consultants

Axiom is seeking a Machine Learning Scientist to support the Environmental Modeling Center (EMC) of the National Centers for Environmental Prediction (NCEP) in building the world's most advanced weather forecasting system through a data-driven approach, working within a multi-disciplinary team committed to open science and actively sharing results with the broader weather and climate communities.

Responsibilities:

• Collaborate with the EMC team to advance the state of the art in weather forecasting through a data-driven approach.
• Identify and prototype promising machine learning approaches from the broader research community.
• Conduct experiments, analyze results, and scale up approaches that demonstrate experimental success.
• Establish best practices and workflows for distributed training, ensuring efficient and scalable machine learning models.
• Work with other engineering teams to create efficient and maintainable data-loading pipelines for diverse data types.
• Promote engineering and research best practices through code reviews and by ensuring high-quality code standards.
• Train other scientists on ML capabilities and tools.
• Participate in workshops and conferences on ML.
• Integrate ML tools within EMC modeling suites.
• Develop innovative ML ideas that improve NWS weather and climate forecasting capabilities.

Requirements:

• MS, or PhD in computer science, mathematics, applied statistics, machine learning, physical science, or equivalent industry experience.
• Strong experience in developing and working with ML tools, especially for earth science problems.
• Experience in working with HPC platforms (MPI, OPENMPI etc.).
• A strong knowledge of available ML packages and tools, such as PyTorch.
• Experience in working with and running earth system models.
• Modern software engineering practices (requirements gathering, design, prototyping, version control, integration, testing and documentation).
• Developing software in a UNIX environment.
• Build and testing mechanisms (cmake and ctest).
• Good communication skills in English.
• Ability to work as part of a diverse team that includes software engineers and scientists across different agencies.
• Hands-on experience in applying experimental ideas to real-world problems.
• Deep understanding of machine learning and statistical methods.
• Experience with Python-based ML frameworks such as PyTorch or JAX.
• Competence in running, tracking, and analyzing experiments, with the ability to instrument them with meaningful metrics and visualizations.
• Strong problem-solving skills to troubleshoot and resolve issues in machine learning workflows.
• Flexibility to adapt and pivot across diverse projects as needed.

Great to Have:

• Proficiency with software environment management tools like Conda or Docker.
• Good understanding of modern languages like C++ and newer versions of Fortran (Fortran 95 and later) is a good plus.
• Expertise in developing and optimizing data loaders for various storage solutions.
• Experience with distributed, multi-node training for machine learning models.
• Experience with ML architectures such as Graph Neural Networks (GNNs), transformers, and diffusion models.
• Experience with earth system models and data.
• Familiarity with the fundamentals of numerical weather prediction systems.

Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities

The contractor will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor's legal duty to furnish information. 41 CFR 60-1.35(c)