Lead the design and execution of microkinetic and reactor-level modeling workflows to translate atomistic simulations into process-scale predictions. Partner with industrial clients and internal ML teams to validate models and shape the technical roadmap for catalyst simulation.
SandboxAQ
21 Remote Job Openings at SandboxAQ
Lead the execution of catalysis validation programs by coordinating between computational scientists, ML teams, and external laboratory partners. Manage the end-to-end pipeline from campaign sequencing and partner SOWs to translating technical results into industrial outcomes.
Lead cross-functional operational execution for AI Simulation programs, managing milestones, risks, and dependencies across multiple semiconductor material verticals. Serve as the primary operational interface for government stakeholders, translating technical progress into compliance-grade reporting.
Director of Corporate Development and Strategic Partner Management
SandboxAQ
·
Full Time
·
2 days ago
SandboxAQ
Lead the evaluation and execution of mergers, acquisitions, and strategic partnerships to drive SandboxAQ's growth. Collaborate with executive leadership and technical teams to translate product opportunities into scalable business plans and durable relationships.
Develop large-scale DFT datasets and machine-learned potentials to simulate the reactivity and dynamics of catalytic materials. Collaborate with interdisciplinary teams to optimize catalyst discovery workflows and support industrial client engagements.
The role involves architecting and implementing scientific and ML software to bridge the gap between R&D prototypes and production-ready tools. Responsibilities include managing the full software lifecycle, integrating modules into the simulation platform, and collaborating with domain experts.
Develop and maintain computational chemistry tools, bridging the gap between R&D prototypes and production-ready software. Collaborate with subject matter experts to architect ML software and integrate modules into the simulation platform via CI/CD pipelines.
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.
Senior Machine Learning Engineer, AI Generation Engine
SandboxAQ
·
Full Time
·
12 days ago
SandboxAQ
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.
Translate internal drug discovery research code and prototypes into scalable, production-ready software products. Collaborate within a multi-disciplinary pod to drive the product lifecycle from scientific inception to external deployment.
Develop and maintain data pipelines and models to support quantum navigation solutions and simulation data integration. Collaborate cross-functionally to provide data observability, technical documentation, and lightweight dashboards for diverse stakeholders.
Serve as the operational architect for the AI Simulation business unit, overseeing the BioSim and ChemSim divisions. The role focuses on scaling operational infrastructure, managing multi-million dollar compute budgets, and driving rigorous resourcing and capacity management.
The role involves deploying and validating navigation solutions on operational platforms while serving as the primary technical bridge between customers and internal research teams. You will lead high-impact customer pilots, analyze complex sensor data, and translate performance metrics into actionable narratives for senior stakeholders.
The role involves defining product strategy for AI simulation models by translating complex scientific user needs into clear product requirements. You will drive cross-functional execution, validate product-market fit with lighthouse customers, and partner with GTM teams to scale adoption.
The Product Manager will define and own the delivery of complex product capabilities by translating scientific user needs into clear requirements. They will drive cross-functional alignment across Science, UX, and Engineering teams while establishing product-market fit and managing the strategic roadmap.
The Staff ML Research Scientist will drive the research and development of next-generation deep learning models for protein-ligand co-folding and affinity prediction, while also architecting the integration of these advanced predictive capabilities into SandboxAQ’s software products.
The resident will join an agile engineering team developing novel Magnetic Navigation systems, focusing on characterizing and calculating map errors using state-of-the-art geospatial analysis, particularly magnetic anomaly maps. Responsibilities also include performing detailed trade studies on regional effects and integrating geospatial insights into navigation algorithms.
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.
The role involves applying computational solutions to drug discovery challenges, rigorously validating results, and enhancing the company's technology and Large Quantitative Models for large-scale impact. Responsibilities include translating insights from various computational methods into actionable drug discovery hypotheses and developing/deploying workflows to guide design decisions.
The role involves orchestrating technical delivery by partnering with scientific teams and ensuring the end-to-end execution of client contracts. Additionally, the engineer will architect and develop solutions to automate complex R&D workflows and integrate core technologies into client environments.
