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

• 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

• 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

• 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

• 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

• 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

• 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

• Help trailblaze company efforts in applying AI within conventional compilation pipelines.
• Design and implement AI-based technology addressing core problems of low-level GPU programming.
• Build training pipelines for supervised fine-tuning and reinforcement learning (RL/RLHF-style or policy optimization variants).
• Define model inputs/outputs over compiler low level compiler representations.
• Develop evaluation frameworks to measure code quality, runtime, compile-time overhead, and correctness.
• Intelligent (domain task based) prompt engineering.
• Collaborate with compiler engineers to integrate learned policies into production toolchains.
• Prototype and iterate on model architectures, prompts, and fine-tuning strategies for scheduling and allocation tasks.
• Create datasets from compiler traces, optimization passes, and target-specific performance signals.
• Apply RL techniques to optimize for downstream objectives (performance, spill reduction, instruction-level parallelism, etc.) and run rigorous experiments, ablations, and benchmarking across workloads and hardware targets.

AI Research Engineer – Applied Scientist, Compilers

• Lead applied research and development for the models and datasets at the core of Fiddler's Trust Service and suite of guardrail classifiers and evaluators that customers depend on to keep their LLM and agentic applications safe, accurate, and compliant in production.
• Partner closely with other engineering teams, Product, and Customer Success to build strong relationships with customer data science and ML engineering teams.
• Design, train, and ship production classifiers for safety, security, and quality detection under strict latency and cost constraints.
• Lead the development of synthetic and adversarial dataset pipelines, including novel methods for generating, filtering, and validating data that exposes failure modes our models need to learn.
• Drive the technical direction of generative insights – the LLM- and agent-powered analysis layer that helps customers diagnose what's going wrong in their AI applications and why.
• Contribute to the evaluation and experimentation infrastructure that lets the AI Science team and our customers reliably measure model quality, regression, and drift across rapidly evolving model populations.
• Explore reinforcement learning and preference-based methods where they offer real leverage over supervised baselines.
• Collaborate with Backend and Platform engineers to take research prototypes from notebook to a hardened, scaled, observable service.
• Partner with Product, Solutions Engineering, and Customer Success to translate enterprise customer needs into research problems and translate research results back into product.
• Mentor AI Scientists on the team, raise the technical bar through code review and design review, and represent Fiddler externally through publications, talks, or open-source contributions when appropriate.

Staff AI Scientist

• Implement agentic workflows using leading LLM models and frameworks to automate reasoning and decision-making tasks
• Prototype AI features, converting research concepts into working demos with tools like Copilot, Cursor, and Claude Code
• Support integration of new AI technologies—including Autonomous and Deep Agents—into our platform to maintain technical leadership
• Work closely with cross-functional teams to test prototypes and ensure compliance with Cisco’s security and scalability requirements
• Help accelerate enterprise AI adoption by contributing to reusable agentic tools and patterns for global teams.

AI Research Engineer

• Design and develop sophisticated agentic workflows leveraging state-of-the-art LLM models and emerging frameworks.
• Rapidly prototype new AI features, transforming research concepts into functional demos using AI-native tools such as Copilot, Cursor, and Claude Code.
• Evaluate and integrate the latest advancements in AI—including Autonomous and Deep Agents.
• Collaborate across teams to validate research prototypes, ensuring alignment with Cisco’s security and scalability standards.
• Accelerate AI adoption across the enterprise by creating reusable agentic patterns and tools that empower teams globally.

Senior AI Research, Agentic Engineer

• Propose and implement engineering solutions to ensure delivery of functional, reliable, secure, and performance-optimal GPU clusters to internal researchers.
• Design, develop and maintain engineering solutions to understand the pain points of validating, monitoring and operating GPU clusters at scale.
• Research in traditional AIOps and the emerging Agentic AI, and leverage it to further reduce the operation toil.
• Participate in on-call support for systems, platforms built and owned by the team.

Senior Software Engineer – AI Research Clusters

Staff Machine Learning Engineer, AI Research

• Implement agentic workflows using leading LLM models and frameworks to automate reasoning and decision-making tasks.
• Prototype AI features, converting research concepts into working demos with tools like Copilot, Cursor, and Claude Code.
• Support integration of new AI technologies—including Autonomous and Deep Agents—into our platform to maintain technical leadership.
• Work closely with cross-functional teams to test prototypes and ensure compliance with Cisco’s security and scalability requirements.
• Help accelerate enterprise AI adoption by contributing to reusable agentic tools and patterns for global teams.

AI Research Engineer – Agentic

• Design and develop sophisticated agentic workflows leveraging state-of-the-art LLM models and emerging frameworks to automate complex reasoning tasks
• Rapidly prototype new AI features, transforming research concepts into functional demos using AI-native tools such as Copilot, Cursor, and Claude Code
• Evaluate and integrate the latest advancements in AI—including Autonomous and Deep Agents—to ensure our platform remains an industry leader
• Collaborate across teams to validate research prototypes, ensuring alignment with Cisco’s security and scalability standards
• Accelerate AI adoption across the enterprise by creating reusable agentic patterns and tools that empower teams globally

Senior AI Research Engineer – Agentic

• Help trailblaze company efforts in applying AI within conventional compilation pipelines
• Design and implement AI-based technology addressing core problems of low-level GPU programming
• Build training pipelines for supervised fine-tuning and reinforcement learning (RL/RLHF-style or policy optimization variants)
• Define model inputs/outputs over compiler low level compiler representations
• Develop evaluation frameworks to measure code quality, runtime, compile-time overhead, and correctness
• Intelligent (domain task based) prompt engineering
• Collaborate with compiler engineers to integrate learned policies into production toolchains
• Prototype and iterate on model architectures, prompts, and fine-tuning strategies for scheduling and allocation tasks
• Create datasets from compiler traces, optimization passes, and target-specific performance signals
• Apply RL techniques to optimize for downstream objectives (performance, spill reduction, instruction-level parallelism, etc.) and run rigorous experiments, ablations, and benchmarking across workloads and hardware targets

• Design, train, and deploy robust policies for locomotion, manipulation, and dynamic interactions with the environment.
• Develop core reinforcement learning infrastructure, including scalable training pipelines and evaluation frameworks.
• Design and implement new simulation environments and tasks to support training and deployment of control policies.
• Develop, design, and test imitation learning methods
• Collaborate with Robotics Software and AI engineering teams to develop policies which can be transferred to production

See all jobs on JobTailor

AI Research Scientist, Applied AI

AI Research Intern

Senior Member of Technical Staff – AI Research

Neuromorphic/AI Research Scientist

Senior Machine Learning Engineer, AI Research

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

AI Research Director

Senior Quantum AI Research Scientist, Applied Research

Applied AI Researcher – Multi-Agent Systems

Principal AI Researcher

AI Research Engineer – Applied Scientist, Compilers

Staff AI Scientist

AI Research Engineer

Senior AI Research, Agentic Engineer

Senior Software Engineer – AI Research Clusters

Staff Machine Learning Engineer, AI Research

AI Research Engineer – Agentic

Senior AI Research Engineer – Agentic

AI Research Engineer – Applied Scientist, Compilers

Senior AI Research Engineer