Posting Title Graduate (3-12 month) Intern - Artificial Intelligence for Power System Operations. Location CO - Golden. Position Type Intern (Fixed Term). Hours Per Week 40. Working at NLR NLR is located at the foothills of the Rocky Mountains in Golden, Colorado is the nation's primary laboratory for energy systems research and development. Join the National Laboratory of the Rockies (NLR), where world-class scientists, engineers, and experts are accelerating energy innovation through breakthrough research and systems integration. From our mission to our collaborative culture, NLR stands out in the research community for its commitment to an affordable and secure energy future. Spanning foundational science to applied systems engineering and analysis, we focus on solving complex challenges to deliver advanced, secure, reliable, and cost-effective energy solutions. Our work helps strengthen U.S. industries, support job creation, and promote national economic growth. At NLR, you'll find a mission-driven environment supported by state-of-the-art facilities, multidisciplinary research teams, and strong collaborations with industry, academia, and other national laboratories. We offer robust professional development opportunities, and a competitive benefits package designed to support your career and well-being. Job Description This Grid Automation and Controls group at The National Laboratory of the Rockies (NLR) focuses on conducting high-impact projects to enhance power system modernization. We develop cutting edge solutions and work closely with industry and utility partners to enhance grid reliability, resilience, and security. Our team is looking for an intern who has strong technical background in machine learning (ML) and artificial intelligence (AI), ideally on large language models, natural language processing, and/or foundation models. This is a 3-month internship opportunity with the potential to extend to 12- months. This internship can be done remotely or onsite. Job responsibilities will include but are not limited to: - Collaborating with internal and external stakeholders to advance research projects - Developing innovative AI/LLM solutions to addressing emerging power system needs - Contributing and/or leading the writing of research papers - The ideal candidate should be able to conduct research work independently To learn more about the work this group does, check out the following link: https://www.nlr.gov/grid/distributed-energy-resource-management-systems . Basic Qualifications Minimum of a 3.0 cumulative grade point average. Undergraduate: Must be enrolled as a full-time student in a bachelor’s degree program from an accredited institution. Post Undergraduate: Earned a bachelor’s degree within the past 12 months. Eligible for an internship period of up to one year. Graduate: Must be enrolled as a full-time student in a master’s degree program from an accredited institution. Post Graduate: Earned a master’s degree within the past 12 months. Eligible for an internship period of up to one year. Graduate + PhD: Completed master’s degree and enrolled as PhD student from an accredited institution. Please Note: • Applicants are responsible for uploading official or unofficial school transcripts, as part of the application process. • If selected for position, a letter of recommendation will be required as part of the hiring process. • Must meet educational requirements prior to employment start date. * Must meet educational requirements prior to employment start date. Additional Required Qualifications - The successful candidate will have completed an undergraduate degree and either be enrolled in or recently graduated from a masters degree in computer science, data science, electrical engineering, or related fields, or be enrolled in a PhD program in these fields - Experienced in one of the following: natural language learning, large language models, foundation models, transformer models - Have a good fundamental knowledge of neural networks, state-of-the-art learning algorithms, and their applications to complex systems - Strong in Python programming and other comparable programming languages - Self-motivated and be passionate to learn new things Preferred Qualifications - Experience with other ML/AI techniques, including reinforcement learning and graph neural networks - Experience in using high performance computers, Linux systems - Experience in JavaScript, SQL, MongoDB, and developing interactive web-based dashboard and tools. - Familiar with power systems and know the basics of power flow . 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: / Annual Salary Range: $51,200 - $81,900 NLR 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 Summary Benefits include medical, dental, and vision insurance; 403(b) Employee Savings Plan with employer match*; and sick leave (where required by law). NLR 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. Internships projected to be less than 20 hours per week are not eligible for medical, dental, or vision benefits. * Based on eligibility rules Badging Requirement NLR 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. Intern assignments extending beyond six months will be subject to this requirement. Drug Free Workplace NLR 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 NLR, 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 NLR 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. . Equal Opportunity 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. Reasonable Accommodations E-Verify www.dhs.gov/E-Verify For information about right to work, click here for English or here for Spanish. E-Verify is a registered trademark of the U.S. Department of Homeland Security. This business uses E-Verify in its hiring practices to achieve a lawful workforce.

Tech. Impact. Collaboration. Du findest KI nicht nur spannend, sondern möchtest sie aktiv in Produkte integrieren und ausbauen? Hier entwickelst du echte Features auf Basis von Machine Learning und generativer KI – mit einem agilen Team, das Neues liebt und Verantwortung übernimmt. Was bieten wir? - New Work leben: Finde deinen idealen Arbeitsort- und deine bevorzugte Arbeitszeit, plane deine Workation im EU-Ausland nach Absprache und probiere neue Wege der Zusammenarbeit aus - Camping, Ferienwohnung, Café oder der heimische Balkon sind nur einige von vielen Möglichkeiten. - Arbeiten am Puls der Zeit: Arbeit mit modernen Tools, Methoden und Equipment in einem spannenden Aufgabenfeld. - New-Work-Budget: Dir fehlt im Homeoffice noch ein zusätzlicher Screen, höhenverstellbarer Schreibtisch oder Bürostuhl? Nutze hierfür dein individuelles smapOne-Ausstattungsbudget. - Hybrid Work: Kicker, Tischtennis, Yoga u.v.m. Unsere modernen Offices in Dresden, Hannover, Ulm und Ravensburg bieten dir viel Abwechslung sowie smappies live und in Farbe - du hast allerdings keine "Office-Pflicht". Ist dein Privatleben besser remote lebbar, mach das gerne. - Lebenslanges Lernen: 1:1-Termine für deine persönliche Weiterentwicklung, „Masterplan“ und unsere Company-Bibliothek mit Fachbüchern auf Wunsch. - Step by step on board: Dich erwartet ein strukturiertes, herzliches Onboarding, ein persönliches Mentoring sowie ein offenes Team. - Bleibende Momente: companyweite Offsites, regelmäßig Teamabende und Standortevents laden zum Vernetzen und Socializen ein. - Merch: Lass dich überraschen! - Vorteilsportal: Portal für Angestellte, um bei über 400 Partnerunternehmen bis zu 60 Prozent zu sparen. - Beratung zur Altersvorsorge: Wir bieten dir eine kostenfreie Beratung bei unserem externen Versicherungsexperten sowie einen Zuschuss zu deiner betrieblichen Altersvorsorge an. - Eurorad: Bleib mobil und unterstütze deine Gesundheit mit unseren Eurorad-Leasing-Angeboten. - FIt bleiben: EGYM Wellpass, damit du Vielfalt und Individualität auch beim Sport erleben kannst. Was solltest du mitbringen? - Background: Studium oder Ausbildung in der Informatik bzw. einem anderen MINT-Bereich – oder intensive Auseinandersetzung mit dem Thema. - Coding Experience: Erfahrung in objektorientierter Softwareentwicklung mit C# und Python. - Full-Stack-Mindset: Ganzheitliches Denken – von Datenbank bis Frontend – und bringst neue AI-Funktionalitäten vollständig ins Produkt - Frontend Know-how: JavaScript/TypeScript und CSS – ein Plus, kein Muss. - Build- & Releasemanagement: Du kennst Tools wie Azure DevOps oder Microsoft Azure – oder bist motiviert, dich einzuarbeiten. - LLM Frameworks: Erfahrung mit der Umsetzung von LLM-Frameworks (z. B. LangChain, LangGraph) oder Integration von Large Language Models in Produkte. - Agile Mindset: SCRUM, Azure DevOps oder JIRA – du hast Erfahrung mit modernen Tools & Methoden oder große Lust, dich einzuarbeiten. - Product Development: Echtes Interesse am Produkt und an den fachlichen Anforderungen der Kunden. - Teamplayer: Strukturierte, selbstorganisierte und zuverlässige Arbeitsweise – kombiniert mit agilem Mindset und echter Teamorientierung. - Communication Skills: Sehr gute Deutsch- und Englischkenntnisse in Wort und Schrift – klare, verständliche Kommunikation der Ergebnisse. Das sind deine spannenden Aufgaben - One team, one goal: Arbeiten in einem unserer agilen Teams als Softwareentwickler:in mit Fokus auf AI Integration. - Software Development: Entwicklung neuer Funktionen mit Machine Learning und generativer KI – vom Konzept bis zur Integration ins Produkt. - Clean Code & Testing: Schreiben von sauberem, wartbarem Code inklusive solider Dokumentation und Testabdeckung. - Model Lifecycle: Betreuung unserer KI-Modelle – von der Integration über das Monitoring bis hin zur RAG-Optimierung. - Data Handling: Aufbau und Optimierung relevanter Datenflüsse zur Umsetzung leistungsstarker KI-Features. - Flexibility & Ownership: Aktive Mitgestaltung in einem Team, das Verantwortung übernimmt und Offenheit lebt. - Sharing is caring: Wissen teilen und den Austausch im Team rund um KI-Themen fördern.

Posting Title Graduate PhD (summer/year-round) Intern - AI Foundation Model for Power System Optimization. Location CO - Golden. Position Type Intern (Fixed Term). Hours Per Week 40. Working at NLR NLR is located at the foothills of the Rocky Mountains in Golden, Colorado is the nation's primary laboratory for energy systems research and development. Join the National Laboratory of the Rockies (NLR), where world-class scientists, engineers, and experts are accelerating energy innovation through breakthrough research and systems integration. From our mission to our collaborative culture, NLR stands out in the research community for its commitment to an affordable and secure energy future. Spanning foundational science to applied systems engineering and analysis, we focus on solving complex challenges to deliver advanced, secure, reliable, and cost-effective energy solutions. Our work helps strengthen U.S. industries, support job creation, and promote national economic growth. At NLR, you'll find a mission-driven environment supported by state-of-the-art facilities, multidisciplinary research teams, and strong collaborations with industry, academia, and other national laboratories. We offer robust professional development opportunities, and a competitive benefits package designed to support your career and well-being. Job Description The National Lab of the Rockies (NLR) is thrilled to announce an exciting opportunity for a full-time Ph.D. intern with experience in machine learning, generative AI, foundation model, large language model, power system optimization, graphic neural network for power system modeling. This is your chance to be at the forefront of energy innovation, working alongside a dynamic, multidisciplinary team of experts from NLR and its collaborators. As a graduate intern within the Sensing and Predictive Analytics Group within the Power System Engineering Center (PSEC), you will dive into a groundbreaking project, developing and implementing cutting-edge AI foundation models for power system optimization problems. Your primary mission will be to leverage your expertise in AI foundation models and power system optimization to revolutionize power system operation and planning. Your deep knowledge of generative AI, AI foundation model, graphic neural networks, and power system optimization will be the driving force behind your success in this role. This full-time position offers the flexibility of optional remote work. Key Responsibilities: - Innovate and Optimize: Build best-in-class AI foundation models and generative AI models for power system optimization, using RNN, GAN, and LLMs. - Implement and Impact: Bring your algorithms to life for industry partners, making tangible improvements in learn to optimize domain. - Lead and Collaborate: Manage our project GitHub repository for experiment tracking and code versioning, ensuring seamless collaboration with partners and code excellence. - Share Your Discoveries: Present your groundbreaking results and key findings at workshops, conferences, and in high-quality journals, positioning yourself as a thought leader in the field. . Basic Qualifications Minimum of a 3.0 cumulative grade point average. Undergraduate: Must be enrolled as a full-time student in a bachelor’s degree program from an accredited institution. Post Undergraduate: Earned a bachelor’s degree within the past 12 months. Eligible for an internship period of up to one year. Graduate: Must be enrolled as a full-time student in a master’s degree program from an accredited institution. Post Graduate: Earned a master’s degree within the past 12 months. Eligible for an internship period of up to one year. Graduate + PhD: Completed master’s degree and enrolled as PhD student from an accredited institution. Please Note: • Applicants are responsible for uploading official or unofficial school transcripts, as part of the application process. • If selected for position, a letter of recommendation will be required as part of the hiring process. • Must meet educational requirements prior to employment start date. * Must meet educational requirements prior to employment start date. Additional Required Qualifications - A current PhD candidate in EE, Computer Science, Computer Engineering, Applied Math, or a related analytical domain. - Expertise in Python and its related libraries, such as Tensorflow, Hugging Face, and Pytorch. - Proven experience in power system optimization and AI foundation models. - A comprehensive understanding of learn to optimize topic. - A track record of publishing high-quality research papers. Preferred Qualifications - Hands-on experience in foundation model, generative AI, and LLMs. - Experience in power system optimization. - Knowledge about power system operation and planning. . 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: / Annual Salary Range: $51,200 - $81,900 NLR 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 Summary Benefits include medical, dental, and vision insurance; 403(b) Employee Savings Plan with employer match*; and sick leave (where required by law). NLR 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. Internships projected to be less than 20 hours per week are not eligible for medical, dental, or vision benefits. * Based on eligibility rules Badging Requirement NLR 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. Intern assignments extending beyond six months will be subject to this requirement. Drug Free Workplace NLR 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 NLR, 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 NLR 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. . Equal Opportunity 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. Reasonable Accommodations E-Verify www.dhs.gov/E-Verify For information about right to work, click here for English or here for Spanish. E-Verify is a registered trademark of the U.S. Department of Homeland Security. This business uses E-Verify in its hiring practices to achieve a lawful workforce.

At Made of Storm, we are professional headhunters dedicated to connecting top-tier talent with leading companies in the iGaming industry. Our focus is on identifying and attracting the best professionals who can drive success in this dynamic market. Description We are seeking an experienced EdTech Specialist with a focus on AI to join our international team and create impactful, AI-powered learning solutions that drive measurable performance outcomes across global audiences. You will own the full project lifecycle — from market research and needs analysis with stakeholders, to testing, implementation, and continuous improvement of interactive trainers, simulators, and AI tools. Your Mission - Conduct in-depth market research on EdTech and AI trends: analyze tools, platforms, competitors, and emerging technologies (e.g., adaptive learning systems, AI-driven personalization). - Identify, evaluate, test, and implement interactive trainers/simulators, AI-powered quizzes, gamified modules from platforms. - Identify, evaluate, test and implement EdTech solutions that will cater current needs in L&D - Train internal teams on AI tools: hands-on workshops covering on-demand technical solutions, generative AI, content creation, analytics, and LMS/Confluence integrations. - Support HR teams with AI adoption by providing customized guidance to the needs. - Develop AI integration roadmaps for HR and L&D: recommend workflows for course design, feedback analysis, and performance tracking. - Measure impact: track ROI of implemented tools through metrics like completion rates, engagement scores, and skill retention. Your Unique Contribution - 2+ years in EdTech and AI. - Proven experience researching and implementing tools (e.g., tested 5+ AI platforms in past roles). - Strong technical skills: proficiency with AI models, LMS, design tools, and data analysis. - Training expertise: ability to deliver workshops, create tutorials, and simplify complex AI concepts for non-tech users. - Excellent communication in English and Russian. - Analytical and data-driven mindset with a passion for EdTech innovation. - Autonomy and project ownership What’s in It for You - A dedicated team of industry professionals who foster a friendly culture and a success-oriented mindset. - The ability to choose between fully remote, hybrid, and in-office work arrangements. - Technical equipment provided. - Employee development plans. - Medical insurance & paid sick leaves. - Compensation for professional education. - English classes. - Sports allowance. - Educational support from our L&D team: internal and external trainings and conferences. - Referral program. - Corporate parties and team building events.