AI Research Scientist

• Engage in relevant research and development (R&D) of AI systems, models, and advanced machine learning algorithms that augment physics-driven modeling and simulation systems
• Explore and implement AI-powered simulation tooling in support of AI workflows through reinforcement learning, multi-agent systems, and hybrid modeling approaches
• Collaborate with research, engineering, and product teams to build AI-powered solutions that meet mission-critical modeling and decision-support needs
• Engage in and support the drafting and review of conference and journal articles and presentations, sharing advances with both internal stakeholders and the wider research community.
• Contribute content to technical invention disclosures, including associated narrative, graphics, and engagements in support of patent development
• Perform additional responsibilities (no more than 10% of duties) in support of the company’s technology and product development initiatives.

AI Research Scientist, Applied AI

• Deliver multi-geography projects for healthcare organizations
• Collaborate with Cloud, Software, and Data Engineering teams
• Design, build, and evaluate healthcare solutions
• Develop high-level solution architectures
• Ensure responsible AI practices
• Lead technical discussions and mentor senior resources
• Contribute to a collaborative team culture

Architect ML – AI Researcher

• Architect, train, fine-tune, and evaluate state-of-the-art speech representations and ASR models (e.g., End-to-End Conformer, Whisper, RNN-T, and hybrid CTC/Attention architectures) across multiple global languages
• Design and deploy highly scalable algorithms for dynamic vocabulary insertion, contextual biasing, and language model (LM) personalization to precisely capture customer-specific terminology, acronyms, and product names
• Implement automated framework evaluations to benchmark model performance, rigorously tracking Word Error Rate (WER), Character Error Rate (CER), embedding-based metrics, latency budgets (RTF), and computing efficiency profiles under varying acoustic environments
• Develop pioneering multilingual benchmarks for end-to-end conversational AI agents, including speech-to-text and text-to-speech components
• Partner with core engineering teams to build, optimize, and maintain high-throughput pipelines optimized for both ultra-low latency real-time streaming inference and high-efficiency asynchronous (batch) multi-channel speech analysis
• Translate product requirements into technical AI roadmaps, working hand-in-hand with Product Managers to ship speech-to-text, simultaneous translation, and semantic speech analytics features

AI Researcher / ML Engineer – ASR, Speech Specialist

• Collaborate with a cross-functional group of technologists, product managers, and archivists to shape the future of ethical AI in journalism.
• Use generative AI to surface archival content for contemporary use.
• Partner with RAD to design and prototype workflows that transform unstructured archival data into structured, discoverable assets.
• Establish standards for the ethical use of artificial intelligence with NPR's archival content.
• Prepare digital collections for machine learning and research approaches that pair AI with human editorial judgment and metadata to find new insights from the archive.
• Identify opportunities and build functional prototypes that enable reporters and producers to query historical audio for contemporary reporting.
• Assist in the development of automated workflows to transform unstructured legacy media into a searchable, AI-indexed library.
• Analyze historical data troves to surface evergreen content opportunities and extract narrative leads that support contemporary reporting.
• Evaluate AI outputs and discovery tools for accuracy and bias to ensure technical prototypes maintain archival integrity.

AI Research Intern, Ethics and Readiness

• Architecting and delivering scalable prototypes for various features
• Research, design, and prototype cutting-edge generative AI solutions that enhance CrowdStrike's AI Detection and Response capabilities
• Create, curate, and maintain high-quality datasets for training and evaluating deep learning models; establish data collection pipelines, labeling workflows, and quality assurance processes to ensure dataset integrity
• Conduct experiments to further the capabilities of existing models

Senior AI Scientist – AI Detection and Response

• Define the social media strategy for Lambda’s research program
• Help build the Lambda story through amplifying our voice in research
• Storyboard marketing content relating to AI/ML research
• Edit short form and long form videos to be posted on Lambda accounts
• Provide data-driven arguments for why a certain channel or type of content deserves more investment
• Use AI to increase efficiency in planning, analysis, and quick iteration

AI Research Intern

• Drive foundational and applied research in reasoning engines, planning architectures, and decision-making frameworks at scale.
• Advance techniques in LLM/LRM post-training, reinforcement learning–based decisioning, and knowledge-integrated agents.
• Design methods for plan induction, value estimation, and contingency modeling within intelligent agents.
• Explore and validate protocols for distributed reasoning and joint planning among cooperative agents in multi-agent systems.
• Architect RPD systems that integrate post-trained LLMs/LRMs, graph-structured memory (e.g., KGs), and RL-driven controllers.
• Design recursive task planners, search-based or policy-based reasoners, and belief-state trackers that can interoperate with large model substrates.
• Ensure modularity and extensibility through multi-agent frameworks, agentic substrates, and declarative planning pipelines.
• Define communication protocols, coordination strategies, and cross-agent knowledge alignment mechanisms to foster emergent cooperative intelligence.

Principal AI/ML Researcher – Reasoning, Planning, Decision-making Systems

• design, implement and iterate agentic AI systems with customers
• innovate at the frontier of the field
• create new solutions and define new categories of product with meaningful impact to Salesforce customers
• build and maintain the shared system context that enables AI to operate accurately and reliably

Senior Member of Technical Staff – AI Research

• Design and analyze neuromorphic AI algorithms for robotics, signal processing, control, and learning on edge platforms
• Develop research-quality software artifacts including APIs, kernels, and benchmarking tools that enable collaborative innovation
• Prototype and evaluate approaches under realistic constraints including quantization, sparsity, memory footprint, latency, and energy optimization
• Collaborate with hardware and software engineering teams to translate algorithmic requirements into hardware specifications
• Build experimental pipelines and benchmarks for target use cases with comprehensive baseline and ablation studies
• Communicate results through technical documentation, customer prototypes, and publications in leading conferences and journals
• Contribute to technical thought leadership in neuromorphic computing and present findings to internal and external stakeholders

Neuromorphic/AI Research Scientist

• Working with large-scale datasets, design and develop novel machine learning algorithms particularly in LLM to provide automation of clinical tasks using medical images, electronic medical records, waveforms, and clinical reports.
• Demonstrating algorithms to meet accuracy requirements on general subject population through statistical analyses and error estimation.
• Building prototypes to enable development of high-performance AI algorithms in scalable, product-ready code.
• Initiating/proposing unique and promising deep learning capabilities, developing new and innovative algorithms and technologies, pursuing patents and research publications where appropriate.
• Researching and evaluating emerging technology, industry, and market trends to assist in product development and/or operational support activities.

• Design, train, and evaluate machine learning models across a range of research and applied AI initiatives
• Run rapid, iterative experiments to test hypotheses and surface insights that drive model improvements
• Collaborate closely with researchers and engineers to translate cutting-edge academic advances into practical, production-ready systems
• Build and maintain robust ML pipelines for data ingestion, feature engineering, model training, and evaluation
• Optimize model performance through fine-tuning, hyperparameter search, and architecture experimentation
• Contribute to a culture of rigorous experimentation; tracking results, documenting findings, and sharing learnings with the broader team
• Stay current with the latest developments in ML and AI research, and proactively identify opportunities to apply them
• This position may require stand-by, on-call, or off-hours duties during critical research or deployment milestones

Senior Machine Learning Engineer, AI Research

• Post-training for model development
• Develop novel algorithms that improve model reliability, controllability, and alignment
• Design and run experiments that shape model behavior
• Partner with infrastructure teams to build scalable, reproducible workflows
• Contribute to publications, patents, and external research visibility
• Drive human-in-the-loop evaluation with high annotation quality
• Communicate technical risks, limitations, and trade-offs clearly to leadership

Principal AI Research Scientist – Post-Training, Alignment, Reinforcement Learning

• Drive foundational and applied research in reasoning engines, planning architectures, and decision-making frameworks at scale.
• Advance techniques in LLM/LRM post-training, reinforcement learning–based decisioning, and knowledge-integrated agents.
• Design methods for plan induction, value estimation, and contingency modeling within intelligent agents.
• Explore and validate protocols for distributed reasoning and joint planning among cooperative agents in multi-agent systems.
• Architect RPD systems that integrate post-trained LLMs/LRMs, graph-structured memory (e.g., KGs), and RL-driven controllers.
• Design recursive task planners, search-based or policy-based reasoners, and belief-state trackers that can interoperate with large model substrates.
• Build and evolve stateful, dynamic models that combine supervised learning with online/offline reinforcement, simulation-based rollouts, and symbol grounding.
• Set direction for planning/reasoning infrastructure within the AI/ML platform strategy.

Principal AI/ML Researcher – Reasoning, Planning, and Decision-making Systems

• Work directly with the CEO to develop and drive the AI research agenda
• Attract, recruit, and retain world-class AI research talent
• Execute some of the AI research agenda as an individual contributor
• Nurture connections with the greater AI ecosystem
• Manage the company’s model training compute resources
• Stand up an applied AI research capability within P-1 Defense subsidiary

AI Research Director

• Develop and deploy AI models across the insurance value chain, leveraging both supervised and unsupervised learning techniques.
• Design, implement, and optimize Retrieval-Augmented Generation (RAG) pipelines for AI-driven decision support.
• Utilize Vector Databases and Knowledge Graphs to enhance AI applications in underwriting, claims processing, and customer engagement.
• Develop data pipelines for ingestion, transformation, and storage to support AI/ML workloads.
• Design and implement scalable solutions using cloud-based AI platforms such as Azure Machine Learning, Databricks.
• Implement MLOps best practices, including CI/CD for model training, validation, deployment, and monitoring.
• Develop generative AI models for personalized customer experiences and automation of complex decision-making processes.
• Apply natural language processing (NLP) techniques to analyze and extract insights from unstructured data sources.
• Optimize AI models for performance, scalability, and reliability in enterprise environments.
• Conduct architecture design reviews and performance tuning for AI/ML applications
• Work cross-functionally with business and technology teams to identify AI-driven opportunities and define strategies.
• Ensure compliance with ethical AI principles, model governance, and data privacy regulations.
• Demonstrate behaviors consistent with PEMCO's policies, values, code of ethics and business conduct.
• Authentically support the PEMCO Brand and constantly are on the lookout for top talent to join us to achieve our Mission to Worry Less and Live More.
• Other duties as assigned.

Senior Data and AI Scientist

• Design and architect AI/ML models for quantum error correction and logical operation synthesis
• Develop AI techniques for quantum computing
• Create high-quality, large-scale datasets
• Collaborate with quantum hardware teams

Senior Quantum AI Research Scientist, Applied Research

• The Multi-Agent Systems team focuses on designing architectures in which multiple agents coordinate to solve problems that require structured interaction across multiple reasoning processes. Researchers build systems that structure communication, route information, and coordinate decision-making across agents operating with different views of the problem
• Researchers in Multi-Agent Systems investigate the interaction patterns that govern how agents collaborate. They study how agents exchange information, critique and refine each other’s reasoning, and coordinate execution across complex workflows. Their work identifies the mechanics behind effective communication, delegation, and coordination, in effect establishing the design language for how systems of agents can operate as cohesive, high-performing teams, with capabilities that arise from interaction rather than individual performance.

Applied AI Researcher – Multi-Agent Systems

• Design, prototype, and evaluate applied AI solutions across natural language, vision, recommendation, and structured data domains.
• Translate ambiguous business problems into well-scoped ML formulations with clear success metrics and evaluation strategies.
• Stay current with the latest research in deep learning, large language models, and adjacent areas, and assess applicability to internal use cases.
• Implement rigorous experimentation workflows including baselines, ablations, and statistically sound evaluation methodology.
• Build production-quality training and inference pipelines using modern ML frameworks and orchestration tools.
• Collaborate with ML platform engineers to ensure efficient use of compute, storage, and accelerator resources.
• Optimize models for accuracy, latency, throughput, and cost based on production requirements.
• Develop tooling for dataset construction, labeling, validation, and ongoing monitoring of data quality.
• Partner with product, design, and domain experts to ensure model behavior aligns with user needs and policy requirements.
• Implement safety, fairness, and reliability evaluations and incorporate findings into model selection decisions.
• Document research findings, design decisions, and operational characteristics clearly for both technical and non-technical audiences.
• Mentor engineers on applied ML methodology, evaluation rigor, and responsible deployment.
• Contribute to internal knowledge sharing, reading groups, and prototype-to-production playbooks.
• Influence the broader AI roadmap based on research insight, capability gaps, and emerging opportunities.

AI Research Engineer – Applied AI

• Define research direction in Agentic AI and LLMs.
• Advance the state of the art in agentic systems, including retrieval, grounding, memory, context, personalization, etc.
• Foundational Model Research: Advance Workday’s proprietary capabilities in pre-training, post-training (RLHF, DPO), and domain-specific alignment for HR and Finance workflows.
• Publish & Open Source: Lead Workday’s contribution to the global AI community through publications at top-tier venues (NeurIPS, ICLR, ICML, ACL, etc.) and strategic open-source releases.
• Research-to-Production Bridge: Partner with Agent Factory engineering pods to integrate SOTA research into production-ready services that scale to the world's largest organizations.
• Mentorship & Culture: Act as a force multiplier for the newly formed research team, fostering a culture of scientific rigor, curiosity, and high-velocity experimentation.

Principal AI Researcher

• Serves as the visionary leader in Bioinformatics AI application development in a clinical genetic testing setting.
• Provides technical guidance and hands-on support towards building company’s next-generation bioinformatics AI platform.
• Identifies, prototypes, and develops state-of-the-art AI applications to revolutionize clinical testing and genomic analysis workflow.
• Designs, develops, evaluates, and deploys novel AI solutions to gain valuable data insights based on the genetical, phenotypical, and clinical datasets.
• Evaluates, adopts, and customizes GenAI models based on both internal and external datasets to build next-generation clinical genetic testing platforms.
• Supports both internal and external data requirements by leveraging AI and GenAI capabilities to keep up with the increasing demands of the business.
• Collaborates in a multidisciplinary and regulated clinical diagnostics environment with geneticists, bioinformaticians, software engineers, and IT infrastructure professionals.

See all jobs on JobTailor

AI Research Scientist, Applied AI

Architect ML – AI Researcher

AI Researcher / ML Engineer – ASR, Speech Specialist

AI Research Intern, Ethics and Readiness

Senior AI Scientist – AI Detection and Response

AI Research Intern

Principal AI/ML Researcher – Reasoning, Planning, Decision-making Systems

Senior Member of Technical Staff – AI Research

Neuromorphic/AI Research Scientist

AI Research Intern

Senior Machine Learning Engineer, AI Research

Principal AI Research Scientist – Post-Training, Alignment, Reinforcement Learning

Principal AI/ML Researcher – Reasoning, Planning, and Decision-making Systems

AI Research Director

Senior Data and AI Scientist

Senior Quantum AI Research Scientist, Applied Research

Applied AI Researcher – Multi-Agent Systems

AI Research Engineer – Applied AI

Principal AI Researcher

Lead Bioinformatics AI Scientist