Machine Learning Engineer II

University Corporation for Atmospheric Research; United States; Hybrid; USD 113,000 - 142,000; Full time

Benefits offered by this job

Health insurance

Dental

Retirement plan

Leave plans

Tuition assistance

Employee assistance programs

Public service loan forgiveness (PSLF)

Job summary

UCAR is seeking a Machine Learning Engineer II to design and develop advanced ML software for Earth System Science applications. You will train, evaluate, deploy, and operate models on large-scale datasets using HPC resources, and collaborate with scientists and engineers to translate scientific requirements into reliable software solutions.

The role requires building reusable tools, APIs, and workflows, and maintaining documentation and best practices for scalable ML systems across projects.

Qualifications

• Demonstrated proficiency applying machine-learning methods to practical problems.
• Proficiency in developing reliable, maintainable software with testing and documentation.
• Ability to analyze AI/ML models and data to make sound technical decisions.

Responsibilities

• Design scalable machine learning software and systems for Earth System Science.
• Train, evaluate, and deploy ML models using large datasets and HPC resources.
• Develop robust workflows for data preparation, training, evaluation, inference, and deployment.
• Create reusable tools, libraries, APIs, and workflows to integrate ML into applications.
• Collaborate with scientists, engineers, and domain experts to translate requirements into software.
• Analyze and optimize performance including GPU utilization and scalability.
• Develop and maintain technical documentation and developer resources.

Skills

Machine Learning

Software Development

Collaboration

Education

Bachelor’s degree + 4 years experience or Master’s

Job description

Position Type: Term - 6 months or more (Fixed Term)

Visa Sponsored Job: No

Relocation Assistance Eligible: Yes

Hiring Range: 113,470.00 USD - 141,840.00 USD

*Final salary and rates are based on education, experience, and skills relevant to the role.

Application Closes at 12:00am MST on: 2026-11-01

About the Role

Great Opportunity! We are seeking a Machine Learning Engineer II. This role will independently design and develop advanced machine learning software and systems for Earth System Science applications. Develop robust, scalable, maintainable software to train, evaluate, deploy, and operate machine learning models using large-scale Earth science datasets and high-performance computing resources. Leads technical implementation for projects and collaborates with scientists, software engineers, and domain experts to translate scientific requirements into reliable computational solutions. May contribute to developing established community tools, frameworks, workflows, and infrastructure. This is a Regular, 2-Year Term position.

Key Responsibilities

• Designing and implementing scalable machine learning software and systems to address complex Earth System Science problems.
• Train, evaluate, and deploy machine learning models and associated software components using modern programming languages, frameworks, and software engineering practices.
• Developing robust workflows and infrastructure for machine learning data preparation, model training, evaluation, inference, and deployment.
• Developing reusable software tools, libraries, APIs, and workflows that enable researchers and developers to incorporate machine learning into Earth System Science applications.
• Collaborating with scientists, software engineers, and domain experts to translate scientific requirements into well-designed, maintainable software solutions.
• Analyzing and optimizing the performance of machine learning applications, including computational efficiency, memory utilization, I/O, scalability, and GPU utilization.
• Develop and maintain technical documentation, examples, and developer- and user-facing resources for machine learning software and systems.
• Maintaining current knowledge of machine learning engineering practices, software frameworks, computing technologies, and approaches relevant to Earth System Science.

Education & Experience

REQUIRED: Bachelor of Science degree and 4 years of related experience, or Master’s Degree; or an equivalent combination of education and experience.

Knowledge, Skills, and Abilities

REQUIRED: Demonstrated proficiency applying machine-learning methods and frameworks to practical problems, including model training, technical evaluation, and inference.

Proficiency in developing 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.

Preferred Qualifications

• Experience implementing and optimizing machine learning workflows for large-scale datasets and high-performance computing environments.
• Experience collaborating effectively with scientists, software engineers, and other technical and domain experts to develop solutions to complex Earth System Science problems.
• Experience leading small technical teams through the software development lifecycle, from requirements and design through implementation, testing, deployment, and maintenance.
• Experience designing and implementing automated workflows for data preparation, model training, evaluation, inference, and deployment.
• Experience with software engineering practices for reliable, maintainable scientific software, including testing, continuous integration, version control, documentation, and reproducibility.

For sponsored positions: UCAR can sponsor individuals for H-1B status only if they are already in the U.S. in H-1B status or another visa status that allows them to change to H-1B status within the U.S.

UCAR is unable to sponsor new H-1B visas for individuals who are outside the U.S. and need to obtain H-1B status through Consular Processing.

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.

Benefits Overview

• Health insurance
• Dental
• Retirement plan
• Leave plans
• Tuition assistance
• Employee assistance programs: Medical, Dental, Vision, and Short & Long Term Disability Insurance
• Generous retirement plan - UCAR contributes 10% of base salary
• Time Off Plans - Minimum 20 days of annual PTO, 10 paid holidays, 12 weeks of paid parental leave, FAMLI Leave
• Tuition Assistance Program
• Public Service Loan Forgiveness (PSLF) eligible employer

UCAR is an Equal Opportunity Employer and welcomes applications from all individuals.

We do not discriminate on the basis of race, age, sex, gender identity, disability, veteran status, or any other characteristic protected by law.

Applicants are not required to provide age-related information (like date of birth or graduation dates) in initial submissions.

At NCAR - the National Center for Atmospheric Research - we study weather, water, climate, air quality, and space weather to help protect lives and livelihoods, grow the economy, and enhance our nation’s security and well-being.

We collaborate with research partners to advance the science that makes predictions better and with end users to develop applications for forecasters, farmers, resource managers, retailers, the military, and many other stakeholders.

UCAR - the University Corporation for Atmospheric Research - manages NCAR on behalf of the National Science Foundation.

We are a nonprofit consortium of more than 115 colleges and universities with research and training programs in Earth system science.

We bring together the academic community and provide the operational management that are both essential to NCAR's success.

UCAR's community programs, from educational resources to data delivery and other services, extend the reach and impact of NCAR's world-class research to the community and society.

We seek talented people with diverse backgrounds, training, and skills to join us in our mission of science in service to society.

Want to learn more? Visit ucar.edu.