Lead product strategy and execution for financial risk modeling and quantitative AI, partnering with customers and technical teams to discover, prototype, and launch high-impact products in ambiguous environments.
Sandboxaq jobs
SandboxAQ uses AI and advanced computing to develop technologies for societal challenges.
35 open roles at Sandboxaq
Own and develop the companyβs intellectual property function, leading patent portfolio strategy and partnering with technical teams to protect innovations and guide product, commercial, and corporate decisions.
Leads ChemSim product strategy and commercial growth, delivering CHIPS Act milestones while building a product-led materials discovery business across semiconductor and adjacent industry markets.
Lead platform architecture and infrastructure strategy for scalable AI workloads, building reliable foundational services while mentoring engineers and improving developer velocity across the organization.
Own partner-facing validation and candidate ranking for PFAS alternatives, applying semiconductor materials expertise to guide AI-driven discovery and turn experimental results into actionable improvements.
Own and grow AISimβs full-funnel demand engine, building multi-channel campaigns and measurement from the ground up to increase sourced and influenced pipeline among technical and scientific B2B audiences.
Own the end-to-end machine learning lifecycle, building and deploying scalable models, data pipelines, and agentic frameworks while rapidly evaluating solutions for AI-first products.
Own the end-to-end machine learning lifecycle, building and deploying scalable models, data pipelines, and AI-first products powered by Large Quantitative Models and agentic frameworks.
Lead product strategy and 0β1 development for AI-powered financial risk and simulation products, partnering with customers, researchers, and engineers to validate use cases and deliver impactful solutions.
Own the end-to-end machine learning lifecycle, building and evaluating models, data pipelines, and agentic frameworks and bringing AI-first products from experimentation into scalable production.
Own the end-to-end machine learning lifecycle for AI-first products, from data pipelines and model development through evaluation and scalable production deployment, using Large Quantitative Models and agentic frameworks.
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