AI Research Scientist

• Ship applied AI from problem definition through deployed production
• Own one or more high-leverage initiatives per quarter with clear KPI hypotheses and delivery accountability
• Mentor junior scientists and influence technical standards within your initiative scope
• Identify high-leverage AI opportunities using business context, data diagnostics, and technical feasibility
• Design practical AI/ML solutions with clear trade-offs on accuracy, latency, cost, and reliability
• Partner closely with product, engineering, analytics, and operations to align scope, sequencing, and accountability

Senior AI Scientist

• Build, validate, deploy, and scale AI/ML models for high-impact manufacturing engineering, research and development applications.
• Lead technical work across a broad set of AI domains, including classical machine learning, deep learning, GenAI, Large Language Models, multimodal AI, agentic AI, World Models, and physics-based AI.
• Translate business and engineering problems into practical AI/ML solution strategies and executable technical plans.
• Serve as a technical authority on model development, deployment architectures, data strategy, evaluation methods, and responsible AI practices.
• Generate new concepts and ideas while conducting research programs that apply the latest AI/ML tools.
• Drive technical assignments in a resourceful and timely manner with minimal supervision.
• Work well with fellow researchers, centers, operational groups, plant personnel and universities.
• Maintain state-of-art technical skills and knowledge.
• Develop working relationships with internal and external subject matter experts.
• Effectively communicate and detail results through internal and external publication.
• Collaborate with global technical teams and lead discussions as an expert in manufacturing AI/ML.

Senior AI/ML Researcher

• Your mission will be to transform Neon’s unique data streams into the gold standard for AI training and evaluation.
• You will bridge the gap between our 500,000+ mobile users and the world’s leading AI labs, by directly interfacing and collaborating with your peers in these labs.
• You will define our research agenda, establishing Neon as a premier authority in audio data research and evaluation science.
• You’ll lead the development of AI assisted evaluation pipelines to characterize and validate the data our platform generates, ensuring it solves the "data bottleneck" for frontier AI models.

Senior Speech AI Researcher

• Collaborate with research mentors to formulate research projects or novel applications of machine learning aligned with the team's mission, with a focus on AI applied to medicine, finance, or law
• Conduct independent and collaborative research and publish high-quality work at top AI and domain-applied research venues
• Design and execute large-scale experiments using modern deep learning frameworks, writing high-quality, reusable code
• Develop models and systems that bridge AI capabilities with real-world application requirements in high-stakes, regulated domains
• Engage across teams — including with domain experts and applied engineering — to ground research in practical constraints and real-world impact
• Contribute to the broader research community through publications, open-source releases, and collaboration with academic and industry partners

Post-Doctoral AI Researcher – 2 year Fixed-Term

• Design and implement end-to-end model pipelines to production across multiple product domains, including ranking, recommendations, search, and personalization
• Develop and maintain scalable data pipelines, data quality checks, and model monitoring to ensure reliability, performance, and responsible behavior of ML systems in production
• Collaborate with cross-functional partners (product, analytics, engineering) to translate ambiguous business needs into well-scoped ML projects, communicate findings, and influence decision making with data-driven insights
• Use A/B tests and offline/online evaluation frameworks to measure model impact and guide iterative improvement

Machine Learning Scientist III – Whole Trip AI

• Guide and screener programming — build out discussion guides and screeners in the Outset platform
• Guide refinement and development — sharpen and iterate on research guides, async or live
• Participant recruitment management and fielding — manage recruitment and keep projects fielded and on track

Research Contractor – AI-Moderated Research

• Frame decision problems, not just research questions; clarify decisions, assumptions, and key tradeoffs.
• Assess project scope, form appropriate research questions, and identify appropriate research methods (developing new methods if/where needed and using GenAI tools to accelerate research workflows).
• Run research studies from start to finish, including developing a realistic research plan and materials, recruiting participants, and synthesizing data into actionable insights.
• Build alliances across the company to identify new partners, drive teamwork, and deeply understand the business context of research problems.
• Advocate for the customer by articulating research findings and product ideas through clear and insightful presentations.
• Translate insights into concise, executive-ready narratives that foster alignment across product, design, and cross-functional leadership partners.
• Mentor junior staff and supervise contractors/vendors on more complicated programs of study.

Staff UX Researcher, AI

• Turn ambiguous healthcare, product, and operational problems into well-posed ML, AI, ranking, optimization, NLP, or LLM-based tasks
• Build strong baselines and improve on them efficiently using the right modeling approach for the problem
• Develop models across traditional ML, deep learning, NLP, and LLM-based approaches where appropriate
• Design offline and online evaluations that are honest, measurable, and predictive of real-world impact
• Choose metrics suited to imbalanced, delayed, noisy, and partially observed healthcare outcomes
• Run careful error analysis and use it to improve model quality, product fit, and operational usefulness
• Identify label leakage, selection bias, confounding, and other data artifacts before they reach production
• Explore messy real-world data, assess label quality, and determine whether a problem is ready for modeling
• Partner with ML engineering to productionize models reliably and define what production-readiness requires
• Work with clinical stakeholders and subject-matter experts to validate assumptions, review model errors, and understand edge cases
• Explain model tradeoffs, uncertainty, limitations, and expected impact clearly to product, operations, clinical, and leadership teams
• Write experiment docs, summarize findings, and help teams make informed decisions about when and how to deploy AI systems
• Pressure-test whether results are real, robust, and useful before recommending production use

Applied Scientist, AI

• Contribute to ongoing research projects and help define new research directions
• Develop internal prototypes to test and evaluate methods relevant to embodied AI assurance
• Document research findings in the form of reports, presentations, and scientific publications

AI Research Internship

• Contribute to ongoing research projects and help define new research directions
• Engage with universities to maintain and strengthen ongoing and future research collaborations
• Develop internal prototypes to test and evaluate methods relevant to embodied AI assurance
• Publish scientific results and attend conferences to build new knowledge and share DNV’s work

AI Researcher

• Serve as a lead contributor on the AI Civics program focused on civic action and community control over AI.
• Lead one or more inter-organizational partnerships with national partner organizations working in K-12 education, labor, faith, or advocacy.
• Execute mission-critical co-design and participatory research projects as part of the AI Civics program.
• Collaborate closely with the AI Civics Program Director and team to co-produce educational materials and public-facing outputs.
• Report to organization leadership on the goals of the program and research progress.
• Participate and help plan research team events and public writing and speaking engagements.

Senior Researcher, AI Civics

• Train, evaluate, and deploy machine learning models tasked with scoring short answer and essay student responses to formative and summative test administrations from school districts nationwide
• Monitor performance of deployed machine learning models to ensure consistent, fair, and unbiased scoring in real time and recalibrate deployed models as needed
• Maintain, update, and improve code base used to train and deploy machine learning models
• Evaluate historical model performance and conduct experiments exploring strategies to potentially improve team modeling techniques and approaches
• Research and stay up-to-date on emerging technologies in the NLP space
• Be a thought leader in automated scoring by attending and presenting at conferences

Advanced Specialist, AI Scientist

• Develop AI/ML models to predict structural biomolecular interactions for novel modalities leveraging protein-protein interactions.
• Design innovative AI/ML approaches to predict protein cooperativity, affinity & other biological properties based on structures.
• Develop co-folding models that incorporate structural and non-structural priors using combinations of public and proprietary BMS data.
• Develop AI/ML models that leverage chemoproteomics data contributing to the generation of novel druggability hypotheses for hard-to-drug targets.
• Author scientific reports, and present methods, results, and conclusions to publishable standard.
• Contribute to the planning and execution of collaborative projects with leading academic and commercial research groups worldwide.

Senior Scientist, AI Computational Structural Biology

• Contribute to the research, design, and development of large-scale foundation models for machine-generated data
• Develop and enhance distributed training and inference workflows
• Collaborate with engineering, product, and data science teams to understand requirements
• Share emerging ideas, technical insights, and best practices with teammates
• Take ownership of assigned projects and deliver high-quality results

Applied AI Scientist

• Conduct original research in embodied AI, including learning from warfighter demonstration, reinforcement learning, memory, reward, vision-language modeling, and world modeling
• Build, test, and benchmark large-scale models for perception, decision-making, and control in simulated and physical environments
• Investigate transfer learning and continual learning paradigms across diverse robotic domains
• Collaborate with engineering, robotics, and field teams to integrate research into operational systems
• Lead research strategy and roadmap across key areas of autonomy and machine learning
• Support field tests and data collection campaigns to evaluate system performance in realistic environments

Senior AI Researcher

• Characterize and integrate biomedical data modalities — digital pathology (whole slide images), neuroimaging (PET, structural and functional MRI), omics (genomics, transcriptomics, proteomics, metabolomics), and longitudinal clinical data to develop specialized, domain-specific models for neurodegeneration.
• Build and refine data engineering pipelines that harmonize heterogeneous modalities — reconciling differences in spatial resolution, temporal scale, and dimensionality — into unified analytical frameworks.
• Identify where cross-modal integration produces genuine insight versus where it introduces noise or artifact, establishing ground truth for downstream AI evaluation.
• Critically assess AI-driven literature synthesis and automated “third reviewer” capabilities for detecting methodological weaknesses, logical gaps, and unsupported claims across data modalities.
• Establish standards for how agentic systems incorporate overlooked or contradictory evidence, such as negative findings, failed clinical trials, etc. and evaluate whether these integrations generate genuinely novel hypotheses.
• Design evaluation frameworks for agentic AI systems operating across neuroscience data modalities — assessing whether models can reason credibly across imaging, omics, and clinical evidence.
• Develop benchmarks using synthetic and real-world multi-modal datasets that probe AI co-scientist capabilities under realistic research conditions, testing for robustness, reproducibility, and alignment with expert-level biomedical reasoning.
• Serve as a neurodegeneration domain expert within the AI/ML team, ensuring that model outputs remain anchored to clinically relevant disease questions.
• Translate evaluation findings into actionable guidance for AI system development, bridging computational and experimental perspectives.
• Publish evaluation methodologies and findings in leading journals and conferences (e.g., AD/PD, AAIC, NeurIPS).
• Articulate emerging AI/ML approaches — causal reasoning, intent classification, agentic planning — to diverse audiences with clear framing of practical applications in drug discovery.
• Co-author manuscripts, concept papers, and translational strategy documents.

Translational Postdoctoral Researcher – Agentic AI for Neurodegeneration

• Characterize and integrate biomedical data modalities — digital pathology (whole slide images), neuroimaging (PET, structural and functional MRI), omics (genomics, transcriptomics, proteomics, metabolomics), and longitudinal clinical data to develop specialized, domain-specific models for neurodegeneration
• Build and refine data engineering pipelines that harmonize heterogeneous modalities — reconciling differences in spatial resolution, temporal scale, and dimensionality — into unified analytical frameworks
• Identify where cross-modal integration produces genuine insight versus where it introduces noise or artifact, establishing ground truth for downstream AI evaluation
• Critically assess AI-driven literature synthesis and automated “third reviewer” capabilities for detecting methodological weaknesses, logical gaps, and unsupported claims across data modalities
• Establish standards for how agentic systems incorporate overlooked or contradictory evidence such as negative findings, failed clinical trials, etc. and evaluate whether these integrations generate genuinely novel hypotheses
• Design evaluation frameworks for agentic AI systems operating across neuroscience data modalities — assessing whether models can reason credibly across imaging, omics, and clinical evidence
• Develop benchmarks using synthetic and real-world multi-modal datasets that probe AI co-scientist capabilities under realistic research conditions, testing for robustness, reproducibility, and alignment with expert-level biomedical reasoning
• Serve as a neurodegeneration domain expert within the AI/ML team, ensuring that model outputs remain anchored to clinically relevant disease questions
• Translate evaluation findings into actionable guidance for AI system development, bridging computational and experimental perspectives
• Publish evaluation methodologies and findings in leading journals and conferences (e.g., AD/PD, AAIC, NeurIPS)
• Articulate emerging AI/ML approaches — causal reasoning, intent classification, agentic planning — to diverse audiences with clear framing of practical applications in drug discovery
• Co-author manuscripts, concept papers, and translational strategy documents

• Manage a team of Applied Scientists and Research Engineers, ensuring a high-performance culture.
• Build, mentor, and grow a high-performing team of applied scientists.
• Translate state-of-the-art AI research into scalable, production-ready solutions.
• Partner with Product and Engineering leaders to define and execute the AI-driven product roadmap.
• Oversee scaling of experiment and LLMOps platforms, balancing reusability and innovation.
• Explore emerging technologies, foster experimentation, and share impact and ideas to both technical and non-technical audiences.

Manager, AI and Applied Research

• Support the development of representation learning models to integrate massive-scale hierarchical data with diverse record sets.
• Evaluate and benchmark diverse machine learning models to resolve data conflicts and improve the accuracy of relationship discovery at scale.
• Assist in building scalable ML prototypes that analyze billions of data points to provide automated insights and personalization.
• Develop efficient data pipelines to process and vectorize massive-scale datasets for downstream research and modeling tasks.
• Collaborate closely with senior researchers to document findings and prepare technical reports on model performance and scalability.

Graduate Research Co-op – AI & Representation Learning

• Design and train large scale transformer and hybrid foundation models
• Own model architecture choices across text, multimodal, and emerging paradigms
• Diagnose and resolve training instabilities at scale
• Navigate scaling tradeoffs across data and compute
• Apply strong fundamentals in deep learning and representation learning
• Build models from first principles, not just adapt pre-existing codebases
• Own optimiser and scheduler choices, including AdamW, Lion, Adafactor
• Design and experiment with loss functions including next-token prediction and contrastive objectives
• Design and execute large-scale training using FSDP, ZeRO-3, Tensor parallelism, Pipeline parallelism
• Apply mixed precision (bf16, fp8) and gradient checkpointing

AI Research Scientist jobs in United States

See all jobs on JobTailor

Senior AI Scientist

Senior AI/ML Researcher

Senior Speech AI Researcher

Post-Doctoral AI Researcher – 2 year Fixed-Term

Machine Learning Scientist III – Whole Trip AI

Research Contractor – AI-Moderated Research

Staff UX Researcher, AI

Applied Scientist, AI

AI Research Internship

AI Researcher

Senior Researcher, AI Civics

Advanced Specialist, AI Scientist

Senior Scientist, AI Computational Structural Biology

Applied AI Scientist

Senior AI Researcher

Translational Postdoctoral Researcher – Agentic AI for Neurodegeneration

Translational Postdoctoral Researcher – Agentic AI for Neurodegeneration

Manager, AI and Applied Research

Graduate Research Co-op – AI & Representation Learning

Senior AI Scientist