You will architect and evolve the marketing technology stack while building measurement and operations functions from the ground up. This role involves developing attribution models, managing reporting infrastructure, and collaborating across teams to turn marketing data into actionable business intelligence.
The Background Investigator will partner with HR, Legal, and Information Security teams to identify and quantify personnel risk through comprehensive analytical research. They will manage investigations from intake to final reporting, providing actionable risk determinations to executive stakeholders.
The Senior Counsel will own the end-to-end patent portfolio strategy and partner with scientists to identify patentable innovations. They will also manage outside counsel, conduct freedom-to-operate analyses, and provide legal guidance on commercial and corporate transactions.
The Senior Director will own the end-to-end product strategy, roadmap, and commercial trajectory for the ChemSim AI-driven materials discovery platform. They will lead a team of product managers to deliver on government-funded R&D milestones while building a scalable, product-led commercial business.
You will develop and maintain the infrastructure, tooling, and CI/CD pipelines required to support the operational needs of medical device products. This includes managing in-field Linux kiosk fleets, ensuring regulatory compliance, and providing self-service tools for engineering teams.
The Research Scientist will design and implement computational workflows to investigate catalytic cycles, reaction mechanisms, and structure-selectivity relationships. They will also collaborate with interdisciplinary teams to develop large-scale datasets and machine learning models for homogeneous catalyst discovery.
Lead the architectural strategy for foundational infrastructure and mentor junior engineers to foster a culture of technical excellence. Collaborate cross-functionally to design scalable, secure, and high-performance systems that support large-scale AI workloads.
Lead the architectural strategy for resilient, distributed infrastructure that supports large-scale AI workloads. Mentor junior engineers while driving platform excellence and collaborating cross-functionally to ensure secure and performant systems.
The role serves as the scientific bridge between generative chemistry workflows and external partners to develop PFAS-free semiconductor materials. Key duties include running discovery workflows, ranking candidate molecules, and translating experimental feedback into technical improvements.
Architect, scale, and optimize scientific codebases to power Large Quantitative Models for drug and materials discovery. Transition high-impact research prototypes into robust, production-grade software and orchestrate distributed training pipelines on GPU infrastructure.
Own end-to-end product marketing and demand generation for the AI Simulation business unit, translating complex technical capabilities into buyer-facing value. Develop positioning, create multi-channel campaign assets, and lead product launch planning to drive pipeline growth.
Lead the scientific direction and technical roadmap for the Magnets vertical to develop high-performance permanent magnets. Manage a multidisciplinary team and collaborate with AI platform teams to accelerate materials discovery and experimental validation.
Serve as the technical authority for the end-to-end software stack, spanning embedded firmware, cloud data pipelines, and clinician-facing applications. Lead the engineering team in maintaining high code quality and ensuring strict adherence to medical device regulatory standards.
Lead the product strategy and execution for AI-driven Finance and Risk Modeling, focusing on financial services and insurance. Drive 0→1 innovation by identifying and prototyping high-potential AI use cases across multiple domains.
Lead the end-to-end machine learning lifecycle to design and deploy AI-first SaaS products using Large Quantitative Models. This includes building robust data pipelines, developing novel ML algorithms, and collaborating with cross-functional teams to create real-world MVPs.
Design and manage robust data pipelines and develop novel ML models for Large Quantitative Models and agentic frameworks. Collaborate with cross-functional teams to translate business objectives into actionable ML development and production roadmaps.
The Director will own the product strategy and roadmap for Finance & Risk Modeling efforts, partnering closely with customers to understand their workflows and decision-making processes. They will also lead rapid prototyping and 0→1 product discovery across new AI/LQM use cases, ensuring impactful prototypes are shipped in an ambiguous environment.
