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

• 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

• 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

• 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

• 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

• Tackle real business challenges, collaborate across teams, and contribute ideas that drive results
• Build meaningful relationships through social events, peer engagement, and shared experiences
• Receive guidance from experienced professionals through our dedicated mentorship program
• Participate in a custom onboarding experience and curated learning series

AI Research Intern

• 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

• Advance Visual Perception: Build and fine‑tune models for detection, tracking, segmentation (2D/3D), pose & activity recognition, and scene understanding (incl. 360° and multi‑view).
• Multimodal Reasoning with VLMs: Train/evaluate vision–language models (VLMs) for grounding, dense captioning, temporal QA, and tool use; design retrieval-augmented and agentic loops for perception-action tasks.
• Physical AI & Embodiment: Prototype perception‑in‑the‑loop policies that close the gap from pixels to actions (simulation + real data). Integrate with planners and task graphs for manipulation, navigation, or safety workflows.
• Data & Evaluation at Scale: Curate datasets, author high-signal evaluation protocols/KPIs, and run ablations that make results irreproducible impossible.
• Systems & Deployment: Package research into reliable services on a modern stack (Kubernetes, Docker, Ray, FastAPI), with profiling, telemetry, and CI for reproducible science.
• Agentic Workflows: Orchestrate multi-agent pipelines (e.g., ‑LangGraphstyle graphs) that combine perception, reasoning, simulation, and ‑code generation to ‑selfcheck and ‑selfcorrect.

AI Research Engineer – Vision AI, VLM, Physical AI

• Lead the development of advanced statistical and machine learning models across core insurance domains such as: Pricing and rating Underwriting and risk selection Claims severity, frequency, and fraud detection Customer lifetime value, retention, and growth
• Design end-to-end analytical solutions, from problem formulation and feature engineering to model deployment and monitoring.
• Champion best practices in model validation, explainability, fairness, and performance monitoring, aligned with regulatory and ethical standards.
• Evaluate and select appropriate modeling techniques (e.g., GLMs, gradient boosting, deep learning, survival analysis, Bayesian methods) based on business context.
• Partner with executives, product leaders, and actuarial teams to shape analytics strategy and identify high-impact opportunities.
• Translate complex analytical findings into clear, actionable insights for both technical and nontechnical audiences.
• Influence roadmap decisions by quantifying business impact, risk, and uncertainty.
• Collaborate closely with data engineering and ML platform teams to ensure models are productionized effectively and maintained at scale.
• Define and promote standards for model reproducibility, documentation, testing, and lifecycle management.
• Contribute to the evolution of internal data science tooling, experimentation frameworks, and ML infrastructure.
• Serve as a technical mentor and role model for emerging data scientists.
• Raise the bar for analytical rigor, code quality, and scientific thinking across the organization.
• Foster a culture of curiosity, experimentation, and evidence-based decision-making.
• Demonstrate behaviors consistent with PEMCO's policies, values, code of ethics, and business conduct.

Principal Data & AI Scientist

• Own and pursue ambitious, long-term research goals.
• Develop solutions for real-world, large-scale problems.
• As needed lead teams to deliver on more complex pure and applied research projects.

Research Scientist – Salesforce AI Research

• 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
• Conduct experiments to further the capabilities of existing models

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AI Research Engineer – Applied Scientist, Compilers

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