9 jobs found

Staff Data Scientist Location: Beachwood, OH Shift: Monday - Friday 8am - 5pm (Onsite 4 days a week) (Possible remote for the right candidate) Position Summary: The Staff Data Scientist will be a key role in the Data Science and Analytics team tasked with providing technical leadership for the establishment of enterprise wide capabilities in data science, AI and predictive analytics. The Staff Data Scientist will typically work on 3-5 large projects concurrently that have organization-wide impact. In addition to these projects, the Staff Data Scientist will provide technical consultation, advice and training on all major on-going Data Science and Analytics projects. When required, the Staff Data Scientist will also act as a project manager where vendors, suppliers and consultants are engaged on key strategic and emerging technology initiatives. Major Responsibilities: Identifying High Value Analytics & AI Opportunities Partner with business leaders to identify opportunities where predictive analytics, machine learning, or generative AI can improve productivity, reduce cost, or unlock new capabilities. Develop clear business cases and ROI models to prioritize initiatives and communicate value to senior leadership. Lead Data Science Projects Translate complex business requirements into robust, scalable technical solutions. Select and implement appropriate modeling techniques, including classical ML, deep learning, generative AI, and reinforcement learning where applicable. Oversee the full model lifecycle: data exploration, feature engineering, model development, evaluation, deployment, monitoring, and continuous improvement. Ensure solutions are production ready, maintainable, and aligned with MLOps best practices. Drive organization wide adoption of models and AI systems through clear communication, documentation, and stakeholder engagement. Technical Guidance & Thought Leadership Provide expert consultation on ML algorithms, model tuning, experimentation frameworks, and cloud native data engineering patterns. Mentor data scientists, ML engineers and AI engineers; support skill development in areas such as forecasting, ML modeling, generative AI, vector databases, and modern ETL/ELT workflows. Contribute to the development of internal standards, reusable components, and best practice guidelines. Project Management Develop and maintain project plans, milestones, and communication strategies for strategic initiatives. Facilitate regular updates with stakeholders, executives, and cross functional partners. Coordinate with vendors, consultants, and technology partners when external expertise is required Lead technology change in Data Science, Analytics and AI Evaluate emerging technologies including generative AI platforms, MLOps tools, cloud services, and data engineering frameworks to determine applicability and business value. Recommend and influence adoption of modern, flexible, and scalable technologies that support a unified enterprise data and AI platform. Drive experimentation and prototyping to accelerate innovation and reduce time to value. Qualifications: Master's Degree required; preferred concentrations in Engineering, Operations Research, Statistics, Applied Math, Computer Science, Data Science or related quantitative field. PhD preferred in Engineering, Operations Research, Statistics, Applied Math, Computer Science, Data Science or related quantitative field. 7+ years of experience along with a PhD in a related field OR 10+ years of experience along with a Master's degree in a related field required. Advanced experience developing and deploying machine learning models using Python and modern ML frameworks (e.g., Scikitlearn, PyTorch, TensorFlow). Strong applied expertise across core ML techniques, including regression, tree based models, clustering, deep learning, and NLP. Familiarity with generative AI and LLMs, including prompt engineering, finetuning, embeddings, and vector databases. Solid understanding of MLOps practices, including CI/CD for ML, automated training pipelines, model versioning, monitoring, and model governance. Hands on experience with cloud based ML platforms (AWS, Azure, or GCP) and containerization/orchestration tools such as Docker and Kubernetes. Working knowledge of modern data ecosystems (Snowflake, Redshift) and the ability to collaborate effectively with data engineering teams when needed. Advanced skill in statistical modeling, SQL, and database concepts required. Demonstrated experience leading small technical teams or pods, providing mentorship and technical direction. Familiarity with Logistics industry is preferred. Regular, predictable, full attendance is an essential function of the job Willingness to travel as necessary, work the required schedule, work at the specific location required, complete Penske employment application, submit to a background investigation (to include past employment, education, and criminal history) and drug screening are required. Physical Requirements: -The physical and mental demands described here are representative of those that must be met by an associate to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. -The associate will be required to: read; communicate verbally and/or in written form; remember and analyze certain information; and remember and understand certain instructions or guidelines. -While performing the duties of this job, the associate may be required to stand, walk, and sit. The associate is frequently required to use hands to touch, handle, and feel, and to reach with hands and arms. The associate must be able to occasionally lift and/or move up to 25lbs/12kg. -Specific vision abilities required by this job include close vision, distance vision, peripheral vision, depth perception and the ability to adjust focus. Penske is an Equal Opportunity Employer. About Penske Logistics Penske Logistics engineers state-of-the-art transportation, warehousing and freight management solutions that deliver powerful business results for market-leading companies. With operations in North America, South America, Europe and Asia, Penske and its associates help businesses move forward by increasing visibility and driving down supply-chain costs. Visit Penske Logistics to learn more. Job Category: Information Technology Job Family: Analytics & Intelligence Address: 3000 Auburn Dr Primary Location: US-OH-Beachwood Employer: Penske Logistics LLC Req ID:

KMM - an ISO 9001:2015, CMMI Level 2 certified company - provides high-quality IT consulting services and innovative solutions by using the most effective and modern technologies. We have a core group of Subject Matter Experts with certifications and immense experience in successfully delivering mission-critical solutions. We have extensive industry experience in the financial, insurance, Health IT, media, marketing, retail, and government markets. We have a proven track record in understanding client's business challenges, determine a customer-focused solution, and provide the technical implementation and documentation to bring it to fruition. Position: AI Engineer Location: Reston, VA (3 days a week onsite) Description: Develop and optimize machine learning and deep learning models using frameworks like TensorFlow or PyTorch. Strong skills in programming languages such as Python, R, or Java, essential for developing AI applications. Build and maintain AI pipelines, from data processing to model deployment. Analyze complex datasets to uncover insights and improve model performance. Ability to analyze complex problems and develop effective AI-driven solutions. Deploy AI solutions on cloud platforms such as AWS. Collaborate with technical and business teams to identify AI opportunities and deliver impactful solutions. Deep understanding of deploying AI applications within a CICD environment, specifically AWS. Preferred qualifications: Experience with MLOps tools (e.g., MLflow, Kubeflow). Knowledge of big data technologies (Spark, Hadoop, Databricks). Background in NLP, computer vision, or other advanced AI techniques. Relevant certifications (Coursera, edX, AWS, Azure, Google Cloud). Required qualifications: Strong programming skills in Python, R, or Java. Hands-on experience with machine learning algorithms and frameworks. Familiarity with major cloud platforms for AI deployment. Strong analytical and problem solving skills. Solid foundation in mathematics and statistics. AI Engineer

Staff Data Scientist Location: Beachwood, OH Shift: Monday - Friday 8am - 5pm (Onsite 4 days a week) (Possible remote for the right candidate) Position Summary: The Staff Data Scientist will be a key role in the Data Science and Analytics team tasked with providing technical leadership for the establishment of enterprise wide capabilities in data science, AI and predictive analytics. The Staff Data Scientist will typically work on 3-5 large projects concurrently that have organization-wide impact. In addition to these projects, the Staff Data Scientist will provide technical consultation, advice and training on all major on-going Data Science and Analytics projects. When required, the Staff Data Scientist will also act as a project manager where vendors, suppliers and consultants are engaged on key strategic and emerging technology initiatives. Major Responsibilities: Identifying High Value Analytics & AI Opportunities Partner with business leaders to identify opportunities where predictive analytics, machine learning, or generative AI can improve productivity, reduce cost, or unlock new capabilities. Develop clear business cases and ROI models to prioritize initiatives and communicate value to senior leadership. Lead Data Science Projects Translate complex business requirements into robust, scalable technical solutions. Select and implement appropriate modeling techniques, including classical ML, deep learning, generative AI, and reinforcement learning where applicable. Oversee the full model lifecycle: data exploration, feature engineering, model development, evaluation, deployment, monitoring, and continuous improvement. Ensure solutions are production ready, maintainable, and aligned with MLOps best practices. Drive organization wide adoption of models and AI systems through clear communication, documentation, and stakeholder engagement. Technical Guidance & Thought Leadership Provide expert consultation on ML algorithms, model tuning, experimentation frameworks, and cloud native data engineering patterns. Mentor data scientists, ML engineers and AI engineers; support skill development in areas such as forecasting, ML modeling, generative AI, vector databases, and modern ETL/ELT workflows. Contribute to the development of internal standards, reusable components, and best practice guidelines. Project Management Develop and maintain project plans, milestones, and communication strategies for strategic initiatives. Facilitate regular updates with stakeholders, executives, and cross functional partners. Coordinate with vendors, consultants, and technology partners when external expertise is required Lead technology change in Data Science, Analytics and AI Evaluate emerging technologies including generative AI platforms, MLOps tools, cloud services, and data engineering frameworks to determine applicability and business value. Recommend and influence adoption of modern, flexible, and scalable technologies that support a unified enterprise data and AI platform. Drive experimentation and prototyping to accelerate innovation and reduce time to value. Qualifications: Master's Degree required; preferred concentrations in Engineering, Operations Research, Statistics, Applied Math, Computer Science, Data Science or related quantitative field. PhD preferred in Engineering, Operations Research, Statistics, Applied Math, Computer Science, Data Science or related quantitative field. 7+ years of experience along with a PhD in a related field OR 10+ years of experience along with a Master's degree in a related field required. Advanced experience developing and deploying machine learning models using Python and modern ML frameworks (e.g., Scikitlearn, PyTorch, TensorFlow). Strong applied expertise across core ML techniques, including regression, tree based models, clustering, deep learning, and NLP. Familiarity with generative AI and LLMs, including prompt engineering, finetuning, embeddings, and vector databases. Solid understanding of MLOps practices, including CI/CD for ML, automated training pipelines, model versioning, monitoring, and model governance. Hands on experience with cloud based ML platforms (AWS, Azure, or GCP) and containerization/orchestration tools such as Docker and Kubernetes. Working knowledge of modern data ecosystems (Snowflake, Redshift) and the ability to collaborate effectively with data engineering teams when needed. Advanced skill in statistical modeling, SQL, and database concepts required. Demonstrated experience leading small technical teams or pods, providing mentorship and technical direction. Familiarity with Logistics industry is preferred. Regular, predictable, full attendance is an essential function of the job Willingness to travel as necessary, work the required schedule, work at the specific location required, complete Penske employment application, submit to a background investigation (to include past employment, education, and criminal history) and drug screening are required. Physical Requirements: -The physical and mental demands described here are representative of those that must be met by an associate to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. -The associate will be required to: read; communicate verbally and/or in written form; remember and analyze certain information; and remember and understand certain instructions or guidelines. -While performing the duties of this job, the associate may be required to stand, walk, and sit. The associate is frequently required to use hands to touch, handle, and feel, and to reach with hands and arms. The associate must be able to occasionally lift and/or move up to 25lbs/12kg. -Specific vision abilities required by this job include close vision, distance vision, peripheral vision, depth perception and the ability to adjust focus. Penske is an Equal Opportunity Employer. About Penske Logistics Penske Logistics engineers state-of-the-art transportation, warehousing and freight management solutions that deliver powerful business results for market-leading companies. With operations in North America, South America, Europe and Asia, Penske and its associates help businesses move forward by increasing visibility and driving down supply-chain costs. Visit Penske Logistics to learn more. Job Category: Information Technology Job Family: Analytics & Intelligence Address: 3000 Auburn Dr Primary Location: US-OH-Beachwood Employer: Penske Logistics LLC Req ID:

Sr. Software Developer School of Medicine, Stanford, California, United States Information Technology Services Oct 29, 2025 Post Date 107317 Requisition # Stanford University is seeking an experienced Sr. Software Developer with a strong passion for biomedical informatics and advancing healthcare through the power of AI. This role involves leading the integration of large-scale biomedical data sources-such as radiology and pathology imaging, genomics, and electronic health records (EHR)-into Stanford's clinical data warehouse. The Sr. Software Developer will design, implement, and maintain both front-end and back-end solutions for healthcare applications, ensuring data is Findable, Accessible, Interoperable, and Reusable (FAIR). Key responsibilities include applying AI tools like Natural Language Processing (NLP) and Machine Learning (ML), managing data security, troubleshooting complex technical problems, and collaborating with diverse teams. This position offers the opportunity to contribute to cutting-edge healthcare research while mentoring junior engineers and overseeing critical projects. Duties include: • Propose, conceptualize, design, implement, and develop solutions for difficult and complex applications. • Contribute to all phases of a project, including systems analysis, program design, development, and implementation. Serve as project lead for some projects. • Oversee testing, debugging, change control, and documentation for major projects. • Lead and mentor professional staff, as necessary, working on all phases of application development projects. • Engage in long-term strategic planning.in collaboration with staff and project leadership. • Define complex application development administration and programming standards. • Oversee the support, maintenance, operation, upgrades of applications. • Troubleshoot and resolve complex technical problems. • Review the physical design of existing systems for optimizing performance. • Lead projects, as necessary, for special systems and application development in areas of complex problems. • Work with other technical professionals to develop standards and implement best practices. • Provide innovative programming and analysis. • May mentor junior software developers. - Other duties may also be assigned DESIRED QUALIFICATIONS: • BS in Software Engineering, Biostatistics, Bioinformatics or research-related program • Experience performing data analysis in research analyses and visualization work in a healthcare research or clinical setting • Fluency in SQL, Python and R • Strong knowledge of cloud platforms such as Google Cloud, Azure or AWS • Proficiency in containerization technologies such as Docker and container orchestration platforms like Kubernetes • Experience with CI/CD tools such as GitLab CI/CD or GitHub Actions • Solid programming skills and experience in scripting • Experience with data transformation and workflow tools such as dbt, Airflow or WDL • Strong knowledge of database architecture best practices • Strong interpersonal and communication skills to interact with technical and non-technical stakeholders • Excellent writing and analytical skills • Five years of experience collaborating as a computational biologist or biostatistician • Experience with common data models like OMOP, PCORnet or i2b2 • Experience with ontologies, terminologies, UMLS, or Semantic Web • Familiarity with Cloud computing paradigm • Experience with working in a medical school environment, and working with HIPAA PHI and other clinical EHR databases • Familiarity with LLMs, NLPs, ML, and other AI technologies EDUCATION & EXPERIENCE (REQUIRED): Bachelor's degree and eight years of relevant experience, or a combination of education and relevant experience. KNOWLEDGE, SKILLS AND ABILITIES (REQUIRED): • Ability to quickly learn and adapt to new technologies and programming tools. • Demonstrated experience in designing, developing, testing, and deploying applications. • Strong understanding of data design, architecture, relational databases, and data modeling. • Thorough understanding of all aspects of software development life cycle and quality control practices. • Ability to define and solve logical problems for highly technical applications. • Strong communication skills with both technical and non-technical clients. • Demonstrated experience leading activities on structured team development projects. • Ability to select, adapt, and effectively use a variety of programming methods. • Ability to recognize and recommend needed changes in user and/or operations procedures. PHYSICAL REQUIREMENTS : • Constantly perform desk-based computer tasks. • Frequently sit, grasp lightly/fine manipulation. • Occasionally stand/walk, writing by hand. • Rarely use a telephone, lift/carry/push/pull objects that weigh up to 10 pounds. - Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of his or her job. WORKING CONDITIONS: • May work extended hours, evening and weekends. • Travel on campus to schools/units. The expected pay range for this position is $169,728 to $194,585 per annum. Stanford University provides pay ranges representing its good faith estimate of the salary the university reasonably expects to pay for a position upon hire. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location and external market pay for comparable jobs. At Stanford University, base pay represents only one aspect of the comprehensive rewards package. The Cardinal at Work website ( ) provides detailed information on Stanford's extensive range of benefits and rewards offered to employees. Specifics about the rewards package for this position may be discussed during the hiring process. Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. WORK STANDARDS (from JDL) • Interpersonal Skills: Demonstrates the ability to work well with Stanford colleagues and clients and with external organizations. • Promote Culture of Safety: Demonstrates commitment to personal responsibility and value for safety; communicates safety concerns; uses and promotes safe behaviors based on training and lessons learned. • Subject to and expected to comply with all applicable University policies and procedures, including but not limited to the personnel policies and other policies found in the University's Administrative Guide, . Additional Information Schedule: Full-time Job Code: 4823 Employee Status: Regular Grade: L Requisition ID: 107317 Work Arrangement : Hybrid Eligible

Assistant/Associate Professor in Computer Science (Precision Health and Environment Cluster Hire) Fall 2026 Location: Knoxville, TN, United States Open Date: Aug 28, 2025 Description: The Min H. Kao Department of Electrical Engineering and Computer Science (EECS ) at The University of Tennessee, Knoxville ( UTK ) is seeking candidates for one (1) tenure-track faculty position at either the assistant or associate professor level in computer science. The area of focus is Natural Language Processing (NLP) broadly defined, including AI areas such as Large Language Models and multimodal Generative Artificial Intelligence (GenAI). This search is to recruit a future leader on campus to lead basic research in GenAI and interdisciplinary research at the cross section of GenAI and vast amounts of healthcare records and diverse healthcare/biomedical applications. This search is part of the Precision Health and Environment Cluster Hire across multiple UTK departments. Precision Health and Environment Cluster Hire The University of Tennessee Knoxville is searching for additional faculty to strengthen the university's position as a global leader in Precision Health and Environment research; this position is among them and will begin August 1, 2026. Recruitment into Precision Health & Environment creates opportunities to build bold agendas that advance big ideas. The successful candidate will join a team of approximately 50 established and successful faculty with shared and complementary research interests in artificial intelligence (AI), health informatics, health information and communication, epidemiology, environmental engineering, systems modeling, natural language processing, and machine learning and a strong desire to grow the scholarly and educational impact of their work. For early career faculty, the cluster also offers a unique framework for professional development and mentorship within a rich transdisciplinary environment. For more information about PHE please visit - . The ideal candidate for this position has a collaborative mindset and prioritizes working with colleagues to realize shared research and educational achievements, including large-scale proposals, joint publications, and new transdisciplinary curricular programming. This unique opportunity may include joint appointments in other participating departments. As Tennessee's flagship land-grant institution, UT is particularly interested in recruiting candidates who are deeply connected to the organizations and communities in which their work will have translational impact, as well as those who will contribute to a climate that values diversity and inclusion. Researchers in the PHE cluster have additional collaboration opportunities through the UT Health Science Center, UT Medical Center, Tennessee Institute of Surgical Innovation, Institute for a Secure and Sustainable Environment, the Tennessee Water Resources Research Center, and the Baker School of Public Policy and Public Affairs. In addition, as the leading university partner in UT-Battelle, the management company for Oak Ridge National Laboratory (ORNL), UTK offers extraordinary opportunities for cutting-edge research in science and engineering with the UT-Oak Ridge Innovation Institute (UT-ORII). Through a streamlined IRB process, UTK researchers have access to a unique rEDW (a research Enterprise Data Warehouse) system, which is a result of decade-long continued investment by the University of Tennessee. rEDW includes rich anonymized healthcare data, such as electronic health records (HER) on over 4 million patients, the associated medical imaging, digital radiology and pathology data, the associated location data for social determinants of health study, as well as genomics data on over 13 thousand children linked to EHR data for genotype-phenotype studies. UTK is the state's flagship campus and leading research institution with a strong partnership with the nearby Oak Ridge National Laboratory (ORNL), where many UTK faculty have ongoing joint positions and/or joint research projects. As a strategic investment, UTK is leading the AI Tennessee , a research and education initiative by the State and the University to engage with academic, industry and community partners across Tennessee to leverage the benefits of AI across all disciplines and economic sections. The Tickle College of Engineering (TCE) is in the midst of an unprecedented period of growth and success, including adding over 30 new faculty to the college as part of ambitious hiring campaigns led by Chancellor Donde Plowman and Dean Matthew Mench. The college has set records in research expenditures, enrollment, incoming student GPA, intellectual property development, and USNWR rank in the past three years. New facilities include the state-of-the art Zeanah Engineering Complex, the University of Tennessee Manufacturing and Design Enterprise (TN-MADE) facility, and the Innovation South building now under construction that will house UTK's Fibers and Composites Manufacturing Facility (FCMF). TCE currently has 203 tenure/tenure track and 79 non-tenure track faculty in its nine academic departments and offers 11 undergraduate, 16 MS, and 15 PhD/DE degree programs. Affiliated with TCE and located in Tullahoma, Tennessee, the UT Space Institute is a hub of aerospace and defense research. The college is also home to eight research centers and three interdisciplinary institutes. With approximately 4,300 undergraduate and 1,500 graduate students, the college sits 29th among public universities in the most recent U.S. News and World Report graduate rankings. Faculty in the college have won 29 early career awards (NSF, DOE, DARPA, AFOSR, and ARO) since 2016. In FY24, the college had annual research expenditures of $113.6M. EECS at UTK has 49 full-time T/TT faculty members, three members of the National Academy of Engineering, 15 IEEE Fellows, 13 NSF/DOE CAREER awardees, and 15 ranked in World's Top 2% Scientists as compiled by Stanford. The department has a growing enrollment of more than 1000 undergraduate and 450 graduate students across the three majors of Electrical Engineering, Computer Engineering, and Computer Science. In addition, the department offers undergraduate minors in computer science, cybersecurity, datacenter technology and management, and machine learning. Successful faculty candidates will be expected to contribute to the continued growth and excellence of EECS. UTK is in Knoxville, TN. The city of Knoxville is a hidden gem with an elegant and walkable downtown, rich and varied nightlife, vibrant neighborhoods, eclectic restaurants, and amazing access to outdoor activities of all kinds as well as exciting cultural events throughout the year. Knoxville is within an easy driving distance to Nashville, Atlanta, Asheville, and the Great Smoky Mountains National Park. From Knoxville's TYS Airport, Knoxville has nonstop flights to 24 major US airports, including DC, NYC, Atlanta, Baltimore, Boston, Charlotte, Chicago, Dallas, Denver, Detroit, Houston, Las Vegas, Miami, Nashville, Orlando, Philadelphia, and Phoenix. In addition, Knoxville and the surrounding areas boast great K-12 schools and one of the most highly educated populations in the entire US. With one of the lowest costs of living in the country, Knoxville was recently recognized in U.S. News and World Report as the 29th best place to live in the U.S. In fact, in 2024, US News ranked the State of Tennessee as in fiscal stability, in economy, and in infrastructure. Qualifications: Minimum Qualifications: A PhD degree in Computer Science, Computer Engineering, or a related discipline at the time of appointment.Preferred Qualifications: Candidates with previous experience working in the convergent area of natural language processing, large language models, multimodal machine learning, and healthcare/biomedical applications. For an Appointment at the Assistant Professor rank: The candidate is expected to show potential for obtaining funding for the research programs, and for participation in interdisciplinary teams. The candidate is also expected to show effective, high-quality teaching skills, and ability to effectively mentor undergraduate and graduate students. For an Appointment at the Associate Professor rank: The candidate is expected to have conducted nationally/internationally recognized research works and show strong leadership potential. The candidate is also expected to show effective, high-quality teaching skills, and ability to effectively mentor undergraduate and graduate students. Application Instructions: The application deadline is November 17, 2025. Applications received after the deadline may be considered until the position is filled. Please submit the following items online in Interfolio to complete your application: Cover Letter Curriculum Vitae Research Statement Teaching Statement Names and Contact Information of Three References Questions should be forwarded to the search committee chair, Dr. Jian Huang at . Equal Employment Opportunity Statement: All qualified applicants will receive equal consideration for employment and admission without regard to race, color, national origin, religion, sex, pregnancy, marital status, sexual orientation, gender identity, age, physical or mental disability, genetic information, veteran status, and parental status, or any other characteristic protected by federal or state law. In accordance with the requirements of Title VI of the Civil Rights Act of 1964, Title IX of the Education Amendments of 1972 . click apply for full job details

ML Data Engineer - Healthcare Data Curation & Cleaning (1 Year Fixed Term) School of Medicine, Stanford, California, United States Information Analytics Jun 03, 2025 Post Date 106579 Requisition University is seeking a Big Data Architect 1 for a 1 year fixed term (possibility of renewal) to design and develop applications, test and build automation tools and support the development of Big Data architecture and analytical solutions. About Us: The Department of Biomedical Data Science merges the disciplines of biomedical informatics, biostatistics, computer science and advances in AI. The intersection of these disciplines is applied to precision health, leveraging data across the entire medical spectrum, including molecular, tissue, medical imaging, EHR, biosensory and population data. About the Position: We are seeking an experienced ML Data Engineer to drive the programmatic curation, cleaning, and generation of healthcare data. In this role, you will focus exclusively on developing and maintaining automated, ML-accelerated pipelines that ensure high-quality data ready for machine learning applications. Your work will be pivotal in shaping the integrity of our data and supporting downstream predictive models in a complex healthcare environment. You Will Find This Position a Good Fit If: You are passionate about transforming raw healthcare data into valuable insights. You believe in the critical role of robust data curation in advancing machine learning in healthcare. You thrive in environments where you can work independently on complex data challenges while collaborating with multidisciplinary teams. You are excited to work with patient-level data and embrace challenges related to data diversity and complexity. Duties include: Design Big Data systems that are scalable, optimized and fault-tolerant. Work closely with scientific staff, IT professional and project managers to understand their data requirements for existing and future projects involving Big Data. Develop, test, implement, and maintain database management applications. Optimize and tune the system, perform software review and maintenance to ensure that data design elements are reusable, repeatable and robust. Contribute to the development of guidelines, standards, and processes to ensure data quality, integrity and security of systems and data appropriate to risk. Participate in and/or contribute to setting strategy and standards through data architecture and implementation, leveraging Big Data, analytics tools and technologies. Work with IT and data owners to understand the types of data collected in various databases and data warehouses. Research and suggest new toolsets/methods to improve data ingestion, storage, and data access. Key Responsibilities: Data Pipeline Engineering: Design, implement, and maintain robust pipelines for the programmatic cleaning, transformation, and curation of healthcare data. Develop automated processes to curate and validate data, ensuring accuracy and compliance with healthcare standards (e.g. OMOP CDM, FHIR). ML Data Engineering: Leverage core machine learning techniques to generate datasets, clean existing health records, join heterogeneous data sources, and enhance data quality for model training. Implement innovative solutions to detect and correct data inconsistencies and anomalies in large-scale healthcare datasets. Healthcare Data Expertise: Work extensively with patient-level health data, ensuring that data handling practices adhere to industry regulations and ethical standards. Utilize the OMOP Common Data Model (OMOP CDM) to standardize and harmonize disparate healthcare data sources, enhancing interoperability and scalability. Collaboration & Continuous Improvement: Collaborate closely with data scientists, clinical informaticians, and engineers to align data engineering practices with analytical and clinical requirements. Continuously monitor, troubleshoot, and optimize data workflows to support dynamic research and operational needs. The expected pay range for this position is $157,945 to $177,385 per annum. Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location and external market pay for comparable jobs. At Stanford University, base pay represents only one aspect of the comprehensive rewards package. The Cardinal at Work website ( ) provides detailed information on Stanford's extensive range of benefits and rewards offered to employees. Specifics about the rewards package for this position may be discussed during the hiring process. Consistent with its obligations under the law, the University will provide reasonable accommodations to applicants and employees with disabilities. Applicants requiring a reasonable accommodation for any part of the application or hiring process should contact Stanford University Human Resources at . For all other inquiries, please submit a contact form. Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. Stanford welcomes applications from all who would bring additional dimensions to the University's research mission. DESIRED QUALIFICATIONS: 3+ years of experience in software development and data engineering with a strong focus on data cleaning, transformation, and creation. Proficiency in Python and experience with data processing libraries (e.g., Pandas, Polars, NumPy). Hands-on experience in building and maintaining automated data pipelines for large-scale data processing. Familiarity with machine learning frameworks (e.g., PyTorch, JAX, scikit-learn) as applied to data quality and augmentation tasks. Expertise in working with healthcare data, including familiarity with the OMOP Common Data Model (OMOP CDM). Strong experience in a Linux environment and comfort with UNIX command-line tools. Proven ability to work collaboratively in multidisciplinary teams and communicate technical concepts effectively. PREFERRED QUALIFICATIONS: Experience with cloud platforms (e.g., GCP, AWS, or Azure) and distributed computing frameworks. Proficiency with version control systems (e.g., Git) and containerization tools (e.g., Docker). Familiarity with healthcare data standards and regulatory requirements. EDUCATION & EXPERIENCE (REQUIRED): Bachelor's degree in scientific or analytic field and five years of relevant experience, or a combination of education and relevant experience. KNOWLEDGE, SKILLS AND ABILITIES (REQUIRED): • Knowledge of key data structures algorithms, and techniques pertinent to systems that support high volume, velocity, or variety datasets (including data mining, machine learning, NLP, data retrieval). • Experience with relational, NoSQL, or NewSQL database systems and data modeling, structured and unstructured. • Experience in parallel and distributed data processing techniques and platforms (MPI, Map/Reduce, Batch). • Experience in scripting languages and experience in debugging them, experience with high performance/systems languages and techniques. • Knowledge of benchmark software development and programmable fields/systems, ability to analyze systems and data pipelines and propose solutions that leverage emerging technologies. • Ability to use and integrate security controls for web applications, mobile platforms, and backend systems. • Experience deploying reliable data systems and data quality management. • Ability to research, evaluate, architect, and deploy new tools, frameworks, and patterns to build scalable Big Data platforms. • Ability to document use cases, solutions and recommendations. • Demonstrated excellence in written and verbal communication skills. CERTIFICATIONS & LICENSES: None PHYSICAL REQUIREMENTS : • Frequently sit, grasp lightly, use fine manipulation and perform desk-based computer tasks, lift, carry, push pull objects that weigh to ten pounds. • Occasionally sit, use a telephone or write by hand. • Rarely kneel, crawl, climb, twist, bend, stoop, squat, reach or work above shoulders, sort, file paperwork or parts, operate foot and hand controls. - Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of his or her job. Additional Information Schedule: Full-time Job Code: 4734 Employee Status: Fixed-Term Grade: K Requisition ID: 106579 Work Arrangement : Hybrid Eligible

The Johns Hopkins Data Science and AI Institute (DSAI) is a new pan-institutional initiative at Johns Hopkins to advance artificial intelligence and its applications, in part through investments in the software engineering, data science, and machine learning space. DSAI is focused on revolutionizing discovery by advancing artificial intelligence that evolves collaboratively with human intelligence, combining the strengths of each for the betterment of society and the world in which we live. DSAI will bring together the mathematical, computational, and ethical foundations of AI with the domains of Health & Medicine, Scientific Discovery, Engineered Systems, Security & Safety, and People, Policy & Governance. DSAI seeks a Research Software Engineer - Clinical NLP Specialty with strong academic background and relevant experience in industry or academia focused on designing and building state-of-the art clinical NLP systems. This position supports research initiatives in the development and novel application of NLP and large language models to extract insights from unstructured clinical text using techniques such as named entity recognition (NER), negation detection, structured data extraction, diagnosis prediction, risk stratification, temporal reasoning and phenotyping. The successful candidate will play a critical role in designing, implementing, rigorously evaluating, deploying and maintaining robust and scalable NLP pipelines and models to extract meaningful information from unstructured clinical text in secure environments, with the goal of enabling high-impact solutions across a range of biomedical domains. Experience with large language models - such as fine-tuning, prompt engineering, model evaluation, and adapting foundation models for domain-specific clinical tasks - is desirable, particularly in contexts that demand privacy, robustness, and interpretability. The clinical NLP RSE will work closely with clinicians, informatics researchers, data scientists and other RSEs to ensure NLP systems meet application goals with methodological rigor and scientific reproducibility. DSAI engineers are at the forefront of modern data intensive science, where professionally developed software is rapidly becoming a key ingredient for success. The DSAI initiative includes the build-out of a substantive and professional-scale software engineering capability, and a dramatic increase in infrastructure, both in hardware and in personnel. JHU has long been a world leader in the broader domains of medicine and public health as well as a wide range of science and engineering fields. This combined with our ethos of building out capabilities to have demonstrable global impact (e.g., JHUs Coronavirus Resource Center the award-winning global resource for real-time data and analysis for COVID-19) and other unique large scientific data sets, like the archives for the Sloan Digital Sky Survey and several simulations, will be key leverage points that will make the DSAI successful. Specific Duties & Responsibilities The successful candidates will participate in ground-breaking research projects that need advanced software solutions requiring expertise in software engineering not commonly found in scientific collaborations. The projects will require development of state-of-the art clinical NLP solutions using the latest deep learning libraries trained on state-of-the-art hardware in secure healthcare computing environments. Projects will involve analysis of massive data sets either in the cloud or on premises. Projects will require development of novel NLP software pipelines for processing of unstructured clinical notes. Some projects may require deep engagement, possibly leading to co-authorship on scientific publications, while others may involve a more casual consulting engagement. They may require software solutions developed from scratch or refactoring existing solutions to make them conform to industry standards (quality, efficiency, reusability, robustness, portability, documentation, etc.). It is a high-level goal of DSAI to translate the efforts for the individual projects into frameworks and template patterns for sustainable scientific infrastructure benefiting future projects. Special knowledge, skills, and abilities Strong NLP, LLM, machine learning and deep learning skills. Practical experience building NLP models and pipelines in a secure, HIPPA compliant healthcare environment. Expert-level knowledge of multiple modern NLP and LLM libraries and models. Hands-on experience adapting and fine-tuning large language models for domain-specific clinical applications, with attention to data efficiency, interpretability, and reproducibility. Demonstrated expertise in prompt engineering, evaluation, and benchmarking of large language models, including applying responsible AI principles in clinical or sensitive-data contexts Expert-level knowledge of the Python programming language. Familiarity with or willingness to learn C++ or other languages as may be needed. Familiarity with software containerization technologies such as Docker and Singularity. Familiarity with the Databricks platform. Fluency in the Linux operating system and related tools. Familiarity with modern software engineering best practices, such as Git source control, peer code review, test-driven development, build automation and continuous integration / continuous delivery. Familiarity with cloud development and deployment. Demonstrated leadership and self-direction. Willingness to teach others both informally and in short course format. Willingness to continually learn new tools and techniques as needed. Excellent verbal and written communication. Minimum Qualifications Masters in a quantitative discipline such as computer science, engineering, physics or bioinformatics, with strong scientific computing and/or mathematics background. Three year's experience working in software development in large clinical NLP projects in industry or academia. Additional education may substitute for required experience, and additional related experience may substitute for required education beyond a high school diploma/graduation equivalent, to the extent permitted by the JHU equivalency formula. Preferred Qualifications PhD in a quantitative discipline. Five (5) years' experience as above in clinical NLP. Experience in CUDA GPU programming. Experience authoring open-source Python packages in PyPI. Experience in open-source project governance. Experience in open-source community adoption initiatives. Classified Title: Scientific Software Engineer Job Posting Title (Working Title): Research Software Engineer - Clinical NLP Specialty (Data Science and AI Institute) Role/Level/Range: APPTSTAF/01/ST Starting Salary Range: Commensurate w/exp. Employee group: Full Time Schedule: 37.5 hrs/wk, M-F FLSA Status: Exempt Location: Hybrid/Homewood Campus Department name: DSAI Institute Personnel area: Whiting School of Engineering Total Rewards The referenced base salary range represents the low and high end of Johns Hopkins University's salary range for this position. Not all candidates will be eligible for the upper end of the salary range. Exact salary will ultimately depend on multiple factors, which may include the successful candidate's geographic location, skills, work experience, market conditions, education/training and other qualifications. Johns Hopkins offers a total rewards package that supports our employees' health, life, career and retirement. More information can be found here: . Education and Experience Equivalency Please refer to the job description above to see which forms of equivalency are permitted for this position. If permitted, equivalencies will follow these guidelines: JHU Equivalency Formula: 30 undergraduate degree credits (semester hours) or 18 graduate degree credits may substitute for one year of experience. Additional related experience may substitute for required education on the same basis. For jobs where equivalency is permitted, up to two years of non-related college course work may be applied towards the total minimum education/experience required for the respective job. Applicants Completing Studies Applicants who do not meet the posted requirements but are completing their final academic semester/quarter will be considered eligible for employment and may be asked to provide additional information confirming their academic completion date. Background Checks The successful candidate(s) for this position will be subject to a pre-employment background check. Johns Hopkins is committed to hiring individuals with a justice-involved background, consistent with applicable policies and current practice. A prior criminal history does not automatically preclude candidates from employment at Johns Hopkins University. In accordance with applicable law, the university will review, on an individual basis, the date of a candidate's conviction, the nature of the conviction and how the conviction relates to an essential job-related qualification or function. Diversity and Inclusion The Johns Hopkins University values diversity, equity and inclusion and advances these through our key strategic framework, the JHU Roadmap on Diversity and Inclusion . Equal Opportunity Employer . click apply for full job details

Data Science Analyst 1 Job ID: 292359 Location: Augusta University Full/Part Time: Full Time Regular/Temporary: About Us Augusta University is Georgia's innovation center for education and health care, training the next generation of innovators, leaders, and healthcare providers in classrooms and clinics on four campuses in Augusta and locations across the state. More than 12,000 students choose Augusta for educational opportunities at the center of Georgia's cybersecurity hub and experiential learning that blends arts and application, humanities, and the health sciences. Augusta is home to Georgia's only public academic health center, where groundbreaking research is creating a healthier, more prosperous Georgia, and world-class clinicians are bringing the medicine of tomorrow to patient care today. Our mission and values make Augusta University an institution like no other. Augusta University's distinct characteristics in education and research include real-world experiences and community engagement, as well as a culture of building community, corporate and government partnerships that address health, security, economic and societal concerns locally and across the state. The University System of Georgia is comprised of our 26 institutions of higher education and learning as well as the System Office. Our USG Statement of Core Values are Integrity, Excellence, Accountability, and Respect. These values serve as the foundation for all that we do as an organization, and each USG community member is responsible for demonstrating and upholding these standards. More details on the USG Statement of Core Values and Code of Conduct are available in USG Board Policy 8.2.18.1.2 and can be found online at Additionally, USG supports Freedom of Expression as stated in Board Policy 6.5 Freedom of Expression and Academic Freedom found online at . Location Augusta University Our Health Sciences Campus: th Street, Augusta, GA 30912 Our Summerville Campus: 2500 Walton Way, Augusta, GA 30904 College/Department Information The Medical College of Georgia (MCG) is one of the nation's largest medical schools by class size, with 304 students per class. The MCG educational experience is anchored by the main campus in Augusta, with regional clinical campuses for third- and fourth-year students across the state, and two four-year campuses located in Athens (in partnership with the University of Georgia) and in Savannah (in partnership with Georgia Southern University). MCG's expanding partnerships with physicians and hospitals across Georgia currently provide more than 350 sites where students can experience the full spectrum of medicine, from complex care hospitals to small-town solo practices. MCG and its teaching hospitals also provide postgraduate education to approximately 575 residents and fellows in 50 different Accreditation Council for Graduate Medical Education-approved programs. Our researchers and clinicians focus on what most impacts the health of Georgia's and America's children and adults, including cardiovascular biology and disease, cancer, neurosciences and behavioral sciences, public and preventive health, regenerative and reparative medicine, personalized medicine and genomics. Our physician faculty also share their expertise with physicians and patients at about 100 clinics and hospitals statewide. Job Summary The Department of AI & Health seeks a Data Scientist 1 to join our growing research unit at a transformative time in healthcare research. This position plays a critical role in advancing our computational capabilities and establishing our department as a leader in AI-driven health research. You will work on cutting-edge projects involving medical imaging, electronic health records, genomics, and real-time patient monitoring data, contributing to high-impact research in predictive diagnostics, personalized medicine, and clinical decision support systems. Your work will directly enable grant acquisition, accelerate publication output in top-tier journals, attract doctoral students and postdoctoral fellows, and establish valuable partnerships with clinical departments and external collaborators seeking robust computational capabilities. Responsibilities The responsibilities include, but are not limited to: Application Development and Maintenance Design and implement predictive models using AI/ML techniques on structured and unstructured data (e.g., admissions data, EHRs, radiology reports). Work at the intersection of longitudinal machine learning, multi-modal analysis, clinical informatics, and population health. Conduct comprehensive data preprocessing, feature engineering, and model validation. Evaluate model fairness, bias, and explainability. Translate insights into operational recommendations through dashboards, briefings, and stakeholder presentations. Support strategic initiatives, including student success analytics, department crowding models, and early detection algorithms. Collaboration and Communication Collaborate with clinicians, educators, and administrators to frame problems, understand data needs, and interpret model outputs. Translate insights into operational recommendations through dashboards, briefings, and stakeholder presentations. Required Qualifications Bachelor's degree from an accredited college or university in Computer Science, Biomedical Informatics, Statistics, Engineering, or a related field and one year of related experience. Preferred Qualifications Prior involvement in healthcare, academic operations, or public sector analytics. Familiarity with EHR systems (Epic, Encompass) or academic admissions systems (AMCAS). Knowledge, Skills, & Abilities Demonstrated experience with machine learning, natural language processing (NLP), or AI model development. Proficiency in Python, R, and data manipulation libraries (e.g., pandas, scikit-learn, TensorFlow/PyTorch). Experience working with clinical, academic, or institutional datasets preferred. Excellent communication skills and ability to translate complex technical findings for non-technical stakeholders. Shift/Salary/Benefits Shift: Days/M-F (work outside of normal business hours will likely be required of an employee in an exempt level position) Pay Band: B9 Salary Range: $48,800/annually - $50,000/annually Salary to be commensurate with qualifications of the selected candidate within the established range (generally minimum-midpoint) of the position. Recruitment Period: 11/21/25 - Until Filled Augusta University offers a variety of benefits to full-time benefits-eligible employees and some of our half-time (or more) employees. Benefits that may be elected could include health insurance, dental insurance, life insurance, Teachers Retirement System (or Optional Retirement Plan), as well as earned vacation time, sick leave, and 13 paid holidays. Also, our full-time employees who have been employed with us successfully for more than 6 months can be considered for the Tuition Assistance Program. Consider applying with us today! Conditions of Employment All selected candidates are required to successfully pass a Background Check review prior to starting with Augusta University. If applicable for the specific position based on the duties: the candidate will also need to have a credit check completed for Positions of Trust and or approved departmental Purchase Card usage. Motor vehicle reports are required for positions that are required to drive an Augusta University vehicle. For Faculty Hires: Final candidates will be required to provide proof of completed academic degree(s) as well as post-secondary coursework in the form of original transcript(s). Those candidates trained by a foreign institution will also be required to provide an educational/credential evaluation. All employees are responsible for ensuring the confidentiality, availability, and integrity of sensitive patient, student, employee, financial, business, etc. information by exercising sound judgment and adhering to cybersecurity and privacy policies during their employment and beyond. Other Information This position is also responsible for promoting a customer-friendly environment and providing superior service to our patients, students, faculty, and employees. "Augusta University is a patient-and family-centered care institution, where employees partner every day with patients and families for success." Augusta University is a tobacco-free environment, and the use of any tobacco products on any part of the campus, both inside and outside, is strictly prohibited. Equal Employment Opportunity Augusta University is proud to be an equal opportunity employer welcoming applicants from underrepresented groups, including individuals with disabilities and veterans. How To Apply Consider applying with us today! Select University Faculty & Staff > External Applicants if you are a candidate from outside the university Select University Faculty & Staff > Internal Applicants if you are a current university employee . click apply for full job details

Department: Sch of Nursing - 440100 Career Area : Information Technology Posting Open Date: 10/23/2025 Application Deadline: 01/11/2026 Position Type: Temporary Staff (SHRA) Position Title : AI/LLM Developer/Engineer Position Number: Vacancy ID: S026301 Full-time/Part-time: Full-Time Temporary Hours per week: 40 Position Location: North Carolina, US Hiring Range: $26.04 - $33.85 per hour Estimated Duration of Appointment: 6 months not to exceed 11 months Be a Tar Heel!: A global higher education leader in innovative teaching, research and public service, the University of North Carolina at Chapel Hill consistently ranks as one of the nation's top public universities . Known for its beautiful campus, world-class medical care, commitment to the arts and top athletic programs, Carolina is an ideal place to teach, work and learn.One of the best college towns and best places to live in the United States, Chapel Hill has diverse social, cultural, recreation and professional opportunities that span the campus and community.University employees can choose from a wide range of professional training opportunities for career growth, skill development and lifelong learning and enjoy exclusive perks that include numerous retail and restaurant discounts, savings on local child care centers and special rates for performing arts events. Primary Purpose of Organizational Unit: The mission of the School of Nursing is to enhance and improve the health and well-being of the people of North Carolina and the nation, and, as relevant and appropriate, the people of other nations, through its programs of education, research, and scholarship, and through clinical practice and community service. The University of North Carolina at Chapel Hill School of Nursing has been the leader in nursing education in North Carolina throughout its history. Established in 1950, it was the first school of nursing in North Carolina to offer a four-year baccalaureate nursing degree program followed by the first master's degree program, the first continuing education program for nurses, first doctoral program, and first accelerated BSN option to students with college degrees. Today, the School is renowned for its academic programs, its research and its commitment to clinical and community service within state, national and global communities. Position Summary: The Center for Virtual Care Value and Excellence (ViVE), led by Dr. Saif Khairat, is seeking an AI/LLM Developer/Engineer to join our AI research team. This is an exciting opportunity to contribute to innovative projects at the forefront of healthcare delivery improvement, leveraging Large Language Models (LLMs) and clinical data analysis. About the Position We are looking for individuals with a strong theoretical and practical background in large language models, machine learning, and natural language processing, combined with a collaborative spirit and a drive for problem-solving. You'll join a multidisciplinary team that values diversity and brings together expertise in software engineering, big data, clinical informatics, and medicine. Key Responsibilities Design, fine-tune, and evaluate large language models (LLMs) tailored to domain-specific applications using techniques such as transfer learning, LoRA, and reinforcement learning with human feedback (RLHF). Build intelligent applications powered by LLMs, including chatbots, virtual agents, clinical decision tools, or document analyzers, using frameworks like LangChain, LlamaIndex, or semantic search pipelines. Develop scalable LLM pipelines and infrastructure, including data ingestion, preprocessing, model serving (via GPU/TPU), and continuous performance monitoring. Integrate commercial and open-source LLMs (e.g., OpenAI GPT, Claude, Mistral, LLaMA) via APIs or local deployment into digital health or enterprise systems. Craft and iterate prompts using advanced prompt engineering and chain-of-thought strategies to improve output relevance, tone, factuality, and task completion. Implement retrieval-augmented generation (RAG) architectures to enhance context awareness using vector databases (e.g., Pinecone, FAISS, Weaviate). Evaluate LLM performance using automated and human-in-the-loop methods to assess accuracy, hallucination, safety, and user satisfaction. Collaborate across disciplines with data scientists, UX designers, domain experts, and MLOps to ensure usability, performance, and alignment with real-world needs. Monitor and optimize system performance, including latency, throughput, token usage, and model cost-effectiveness across deployment environments. Stay current with advancements in generative AI, contributing to the internal knowledge base and driving adoption of best practices for ethical and responsible LLM use. Minimum Education and Experience Requirements: Bachelor's degree in Computer Science, Computer Information Systems, Computer Engineering, or closely related degree from an appropriately accredited institution and three years of experience in operations analysis and design, systems programming, or closely related area; or a - Bachelor's degree from an appropriately accredited institution and four years of experience in operations analysis and design, systems programming or closely related area; or an Associate's degree in Computer Information Technology, Computer Engineering Technology, or Networking Technology from an appropriately accredited institution and five years of experience in operations analysis and design, systems programming, or closely related area; or an equivalent combination of education and experience. - Journey level requires an additional one year of education or experience. - Advanced level requires an additional two years of education or experience. Required Qualifications, Competencies, and Experience: Bachelor's degree in Computer Science, Electrical Engineering, or related fields. Expertise in Retrieval-Augmented Generation (RAG), Natural Language Processing (NLP), deep learning frameworks. Proficiency in Python and frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, or LangChain Familiarity with clinical or healthcare data (e.g., EHRs, clinical notes, structured claims data) Proven research record with peer-reviewed publications in relevant fields Strong problem-solving skills and the ability to work in a collaborative environment. Preferred Qualifications, Competencies, and Experience: Distributed parallel training and parameter-efficient tuning. Familiarity with multi-modal foundation models, HITL techniques, and prompt engineering. Experience with LLM fine-tuning, prompt engineering, or retrieval-augmented generation (RAG) Experience deploying large-scale machine learning models in cloud environments. Campus Security Authority Responsibilities: Not Applicable.