Machine Learning Research Engineer – Foundation Models for Science & Engineering

Posting TitleMachine Learning Research Engineer – Foundation Models for Science & Engineering

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LocationCO - Golden

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Position TypeRegular

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Hours Per Week40

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Working at NRELThe National Renewable Energy Laboratory (NREL), located at the foothills of the Rocky Mountains in Golden, Colorado is the nation's primary laboratory for research and development of renewable energy and energy efficiency technologies.

From day one at NREL, you’ll connect with coworkers driven by the same mission to save the planet. By joining an organization that values a supportive, inclusive, and flexible work environment, you’ll have the opportunity to engage through our ten employee resource groups, numerous employee-driven clubs, and learning and professional development classes.

NREL supports inclusive, diverse, and unbiased hiring practices that promote creativity and innovation. By collaborating with organizations that focus on diverse talent pools, reaching out to underrepresented demographics, and providing an inclusive application and interview process, our Talent Acquisition team aims to hear all voices equally. We strive to attract a highly diverse workforce and create a culture where every employee feels welcomed and respected and they can be their authentic selves.

Our planet needs us! Learn about NREL’s critical objectives, and see how NREL is focused on saving the planet.

We invite all interested candidates to apply for this opportunity. While we recognize that job seekers may hesitate if they don’t meet every requirement, we encourage dedicated individuals who meet all the basic and additional required qualifications of the role to submit an application. We value the opportunity to consider those who believe they have the necessary skills and ambition to succeed at NREL.

Job Description

The AI, Learning, and Intelligent Systems (ALIS) Group in the NREL Computational Science Center has an opening for a full-time machine learning research engineer that will contribute to the development of large-scale foundation models for scientific discovery. We aim to fill this role with a dynamic engineer that has a technical background in machine learning and is passionate about using modern machine learning techniques to tackle science’s greatest challenges. The successful candidate has experience implementing, training, and deploying machine learning models on high-performance computing systems and/or the cloud, and running experiments to evaluate the performance of algorithms and models. Familiarity with large language models is preferred. This remote-friendly position includes access to cutting-edge Dept. of Energy high-performance computing (HPC) systems equipped with the latest hardware accelerators for distributed computing.

You do not need to match every listed expectation to apply for this position. We know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.

Responsibilities:

• Operations and research support: design, develop, configure, debug, deploy, and support frameworks and workflows on scalable, accelerated computing hardware and cloud architectures centered on modern machine learning such as large language models.
• Collaboration with researchers: Work closely with research scientists to implement, train, and deploy large-scale machine learning models for scientific discovery.
• Assist with publications: Help run experiments involving the deployment of machine learning models via containerized workflows.
• Collaboration with engineers: Work closely with computing professionals to optimize large-scale model training and inference efficiency on advanced computing hardware.

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Basic QualificationsRelevant Bachelor's Degree and 2 or more years of experience or equivalent relevant education/experience. Or, relevant Master's Degree or equivalent relevant education/experience. General knowledge and application of standards, principles, concepts and techniques in specific field. Some understanding of related IS practices and standards. Skilled in analytical techniques and practices, and problem solving. Skilled in written and verbal communication. Intermediate programming ability with various computer software programs and information systems.

* Must meet educational requirements prior to employment start date.

Additional Required Qualifications

• Skilled in analytical techniques and practices, and problem solving
• Skilled in written and verbal communication
• General knowledge and application of standards, principles, concepts and techniques in software engineering
• Proficient at Git and GitHub
• Experience maintaining large, open-source software projects
• Familiarity with PyTorch and Tensorflow
• Genuine interest in AI4Science and NREL’s mission
• Genuine interest in becoming highly proficient at developing and deploying large language models on HPC and Cloud architectures

Preferred Qualifications

• Ph.D. in computer science, applied math, a related field, or BSc/MSc plus relevant experience
• Familiarity with cloud platforms and services (e.g., AWS, Google Cloud, Azure) for deploying machine learning models
• Experience with containerization and scaling including Docker and Apptainer
• Background and experience in managing software dependencies in HPC and Cloud environments with commons tools such as Modules, Conda, Spack, and containerization
• Background and experience in machine learning, deep learning, generative models, and large language models
• Experience with distributed training frameworks and tools such as DeepSpeed, HuggingFace transformers and accelerate, Megatron, etc.
• Experience writing custom CUDA code and/or ROCm

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Job Application Submission Window

The anticipated closing window for application submission is up to 30 days and may be extended as needed.

Annual Salary Range (based on full-time 40 hours per week)Job Profile: IT Professional II / Annual Salary Range: $79,600 - $143,300

NREL takes into consideration a candidate’s education, training, and experience, expected quality and quantity of work, required travel (if any), external market and internal value, including seniority and merit systems, and internal pay alignment when determining the salary level for potential new employees. In compliance with the Colorado Equal Pay for Equal Work Act, a potential new employee’s salary history will not be used in compensation decisions.

Benefits SummaryBenefits include medical, dental, and vision insurance; short*- and long-term disability insurance; pension benefits*; 403(b) Employee Savings Plan with employer match*; life and accidental death and dismemberment (AD&D) insurance; personal time off (PTO) and sick leave; paid holidays; and tuition reimbursement*. NREL employees may be eligible for, but are not guaranteed, performance-, merit-, and achievement- based awards that include a monetary component. Some positions may be eligible for relocation expense reimbursement. Limited-term positions are not eligible for long-term disability or tuition reimbursement.

* Based on eligibility rules

Badging RequirementNREL is subject to Department of Energy (DOE) access restrictions. All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card as required by Homeland Security Presidential Directive 12 (HSPD-12), which includes a favorable background investigation.

Drug Free Workplace

NREL is committed to maintaining a drug-free workplace in accordance with the federal Drug-Free Workplace Act and complies with federal laws prohibiting the possession and use of illegal drugs. Under federal law, marijuana remains an illegal drug.

If you are offered employment at NREL, you must pass a pre-employment drug test prior to commencing employment. Unless prohibited by state or local law, the pre-employment drug test will include marijuana. If you test positive on the pre-employment drug test, your offer of employment may be withdrawn.

Submission Guidelines

Please note that in order to be considered an applicant for any position at NREL you must submit an application form for each position for which you believe you are qualified. Applications are not kept on file for future positions. Please include a cover letter and resume with each position application.

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EEO Policy

NREL is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, domestic partner status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws.

EEO is the Law | Pay Transparency Nondiscrimination | Reasonable Accommodations

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