Machine Learning Engineer II

Build advanced machine learning systems for Earth System Science with UCAR. This onsite role gives you the opportunity to independently design and develop scalable ML software and systems, working with large-scale Earth science datasets and high-performance computing. You will also help translate scientific needs into maintainable computational solutions while contributing to the workflows and infrastructure that enable researchers to use ML in real applications.

Location: United States (onsite)
Salary: USD 113,470 - 141,840 per year
Position type: Term - 6 months or more (Fixed Term), Regular, 2-Year Term position
Relocation assistance: Eligible
Visa sponsored job: No

What you’ll do

• Design and implement scalable machine learning software and systems to solve complex Earth System Science problems.
• Train, evaluate, and deploy machine learning models and supporting software components using modern programming languages, frameworks, and software engineering practices.
• Develop robust workflows and infrastructure for data preparation, model training, evaluation, inference, and deployment.
• Create reusable tools, libraries, APIs, and workflows that help researchers and developers integrate ML into Earth System Science applications.
• Collaborate with scientists, software engineers, and domain experts to turn scientific requirements into well-designed, maintainable software.
• Analyze and optimize ML application performance across computational efficiency, memory utilization, I/O, scalability, and GPU utilization.
• Develop and maintain technical documentation, examples, and developer- and user-facing resources for ML software and systems.
• Stay current on machine learning engineering practices, software frameworks, computing technologies, and approaches relevant to Earth System Science.

Required qualifications

• Demonstrated proficiency applying machine-learning methods and frameworks, including model training, technical evaluation, and inference.
• Proficiency building reliable, maintainable software using testing, version control, code review, documentation, and reproducibility practices.
• Ability to independently analyze moderately complex AI/ML models, data, software, and computing problems and make sound technical decisions.
• Ability to translate customer or scientific requirements into scoped technical work and communicate trade-offs to varied audiences.

Education and experience

• Bachelor of Science and 4 years of related experience, or
• Master’s Degree, or
• An equivalent combination of education and experience.

Preferred qualifications

• Experience implementing and optimizing ML workflows for large-scale datasets in high-performance computing environments.
• Experience collaborating effectively with scientists and software or domain experts on complex Earth System Science problems.
• Experience leading small technical teams through requirements, design, implementation, testing, deployment, and maintenance.
• Experience designing and implementing automated workflows for data preparation through deployment.
• Experience with software engineering practices for reliable, maintainable scientific software, including testing, continuous integration, version control, documentation, and reproducibility.

Benefits and time off

• Medical, Dental, Vision, and Short & Long Term Disability Insurance
• Generous retirement plan: UCAR contributes 10% of base salary
• Minimum 20 days of annual PTO
• 10 paid holidays
• 12 weeks of paid parental leave
• FAMLI Leave
• Tuition Assistance Program
• PSLF eligible employer

Work schedule and compliance

• All hybrid staff are expected to work on-site approximately 3 days per week.
• All roles require compliance with U.S. export control regulations and work location requirements.

Application details

• Required: Questionnaire, Resume/CV
• For full consideration, all application materials must be submitted by 12am (MST) at the start of the application deadline.
• Supplemental questionnaires are often requested in lieu of a cover letter.
• Background checks and/or federal screenings are conducted for candidates selected for hire.
• Application closes at 12:00AM MST on: 2026-11-01

Equal opportunity: UCAR is an equal opportunity employer and welcomes applications from all individuals. Applicants are not required to provide age-related information (such as date of birth or graduation dates) in initial submissions.

Position specifics: This role supports ML model training, evaluation, deployment, and operations using large-scale Earth science datasets and high-performance computing resources. You may also contribute to developing established community tools, frameworks, workflows, and infrastructure.