AI Research Scientist

• Produce research advances in generative AI to improve models or agents for networking automation, human-computer interaction, model safety, and strategic generative-AI networking areas
• Research domain-specific foundational representations relevant to networking
• Build purpose-built large language models for Cisco’s networking, security, data center, and observability infrastructure
• Drive pre-training initiatives for foundational models across Cisco’s product portfolio
• Conduct innovative generative AI research to improve networking automation and human-computer interaction
• Collaborate with cross-functional engineers and strategists to integrate research breakthroughs into business solutions
• Publish research in top-tier AI venues and contribute to the broader scientific community
• Give technical talks and organize workshops
• Establish Cisco as a global thought leader in AI research

Senior AI Researcher, AISWP

• Investigate challenging technical problems and formulate algorithmic approaches
• Perform literature reviews to identify promising methods and determine how they can be adapted
• Design, implement, test, and improve prototype algorithms using AI, statistics, optimization, estimation, search, signal processing, machine learning, and related techniques
• Analyze complex data and system behavior to identify meaningful patterns and select appropriate computational approaches
• Compare alternative approaches and refine algorithms based on experimental results, theoretical insight, and operational requirements
• Collaborate with scientists and engineers to integrate algorithms into operational software and hardware systems
• Communicate technical approaches, experimental results, and recommendations to technical and non-technical stakeholders
• Stay current with academic research and emerging methods and identify opportunities to apply them to Perceptronics problems

• Define strategy for training data capabilities and prioritize data collection
• Own decisions around data quality, review depth, confidence thresholds, and cost
• Own end-to-end data collection, including procurement, preparation, capture, expert labeling, and annotation
• Build scalable systems across data collection stages
• Coordinate teams and sites to maximize throughput and drive capacity planning
• Define human review processes and feedback loops that convert corrections into training data
• Partner with ML Engineering, Operations, and subject matter experts to set direction and drive execution
• Define metrics for data quality, model improvement, throughput, and cost efficiency
• Communicate progress and tradeoffs to senior leadership
• Mentor Product Managers and contribute to product practices and documentation
• Use Claude Cowork, Claude Code, Codex, and other emerging AI tools and coding agents to accelerate product development and improve workflows

Staff Product Manager, AI Research – Engineering

• Design, develop, and deploy AI-driven applications transforming large-scale geospatial data into actionable insights and predictive intelligence
• Build and operate end-to-end AI/ML pipelines covering data ingestion, preprocessing, feature engineering, training, evaluation, and production inference
• Productionize reasoning models, vision-language models, and multimodal AI systems combining imagery, geospatial signals, and structured data
• Architect enterprise-grade training and experimentation frameworks with automated pipelines, experiment tracking, benchmarking, and reproducible evaluation
• Create synthetic datasets and test harnesses to validate model performance, robustness, and edge-case behavior
• Collaborate with domain experts, software engineers, product managers, research partners, and technology partners
• Optimize models and inference systems for scalability, latency, cost efficiency, and reliability on modern cloud infrastructure
• Implement and maintain production inference systems, including monitoring, model versioning, retraining workflows, and performance tracking
• Track advances in foundation models, generative AI, multimodal learning, and reasoning systems and translate them into practical systems
• Maintain engineering standards through code reviews, documentation, experimentation discipline, and collaborative problem solving
• Help shape next-generation Earth AI capabilities

Principal Applied AI Scientist

• Design and implement data analysis pipelines for data science and machine learning/artificial intelligence
• Meet specifications of faculty or senior staff independently or in collaboration with research staff, trainees, and fellows
• Use modern programming languages on UN*X operating systems
• Work with sensitive data in secure environments while adhering to legal frameworks such as HIPAA
• Design and maintain study databases, including relational databases and data lakes
• Create and maintain documentation for analysis pipelines to facilitate knowledge transfer
• Contribute to research dissemination materials, including manuscripts and presentations
• Contribute to research design materials, including project proposals
• Perform project management or lab management duties according to defined specifications
• Collaborate with on-premises computing professionals to configure and maintain physical systems when needed
• May supervise undergraduate and graduate trainees
• Perform related responsibilities as required

AI Scientist/Engineer II – School of Medicine, BMI

• Investigate the capabilities, limitations, and training methods of frontier AI systems
• Formulate research questions that inform AI products, platforms, and technical strategy
• Explore synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation
• Stay current with advances in machine learning and identify opportunities for technical contributions
• Develop research-grade datasets, experiments, prototypes, tooling, and evaluation frameworks
• Train, test, and evaluate models using modern AI and machine learning tools
• Analyze experimental results and develop evidence-based conclusions
• Establish practices for data quality, reproducibility, experimental design, and evaluation
• Iterate from research hypotheses to validated technical insights
• Collaborate with Research, Engineering, Product, and Operations teams to translate findings into practical applications
• Communicate technical findings to specialized and cross-functional audiences
• Contribute to technical reports, publications, open-source projects, workshops, or conferences where appropriate
• Mentor engineers and researchers and contribute to technical discussions and peer review

Staff Research Engineer – AI & Machine Learning

• Establish technical direction and lead design, development, and operationalization of advanced AI solutions for healthcare operations, patient outcomes, and organizational performance
• Lead evaluation of emerging AI technologies and define enterprise adoption strategies
• Process and analyze unstructured healthcare data using NLP and deep learning techniques
• Provide technical leadership for AI solutions from ideation through enterprise-scale production deployment
• Influence enterprise AI roadmaps and strategy through technical expertise and strategic partnerships
• Establish technical standards, reusable frameworks, best practices, and governance for AI development, deployment, monitoring, and optimization
• Direct complex NLP, predictive analytics, and applied AI initiatives across multiple business domains
• Collaborate with IT, risk adjustment, program integrity, HEDIS, healthcare operations, finance, and clinical teams
• Develop and implement predictive models, algorithms, and statistical techniques using large healthcare datasets
• Define and execute evaluation strategies for ML and LLM solutions, including quality metrics, bias and safety checks, and post-deployment monitoring
• Conduct data cleansing, feature engineering, exploratory data analysis, and rigorous data analysis
• Define KPIs, metrics, dashboards, and reports with stakeholders to support decision-making
• Provide strategic guidance to senior leadership based on predictive modeling and data analysis
• Ensure HIPAA and PHI compliance, data integrity, model governance, and documentation
• Serve as a subject matter expert in AI, machine learning, NLP, Generative AI, and emerging technologies
• Mentor Applied AI Scientists, Data Scientists, and technical teams through code reviews, technical guidance, and architecture recommendations
• Evaluate Responsible AI practices, healthcare AI regulations, and governance requirements
• Perform other job-related duties as requested

Applied AI Scientist IV

• Build purpose-built large language models for Cisco’s networking, security, data center, and observability infrastructure
• Drive pre-training initiatives for foundational models across Cisco’s product portfolio
• Conduct generative AI research to improve networking automation and human-computer interaction
• Research domain-specific foundational representations relevant to networking
• Collaborate with cross-functional engineers and strategists to integrate research into business solutions
• Publish research in top-tier AI venues
• Give technical talks and organize workshops
• Contribute to the broader scientific community and establish Cisco as a global AI research thought leader

AI Researcher, AISWP

• Support a faculty research project examining the adoption and use of artificial intelligence in small and medium-sized businesses in Wisconsin
• Use AI-assisted tools to identify potential research participants
• Organize business and contact information
• Support participant recruitment and data collection
• Assist with other research-related tasks as needed

Student Research Assistant – AI Research Project

• Lead, design, and execute complex user research studies to identify opportunities to drive business value and improve user experience
• Merge qualitative and quantitative data via mixed methodologies
• Present research insights to senior stakeholders and executive leadership to influence product and business decisions
• Synthesize and communicate research findings through executive summaries, workshops, and actionable recommendations
• Partner with designers, product managers, and engineers to translate research insights into strategic design and product roadmaps
• Document insights and artifacts in a central repository
• Lead the creation and evolution of user personas/archetypes and journey maps
• Collaborate with Research Operations to use standardized research materials, frameworks, and processes
• Champion emerging industry trends, tools, and methodologies, especially AI and Agentic technologies
• Report to the Manager, CX/UX Research

AI Research Scientist jobs in United States

Senior AI Researcher, AISWP