SandboxAQ
51 - 200 employees
Founded 2021
🤖 Artificial Intelligence
🔒 Cybersecurity
💊 Pharmaceuticals
Artificial Intelligence • Cybersecurity • Pharmaceuticals
SandboxAQ is a company developing quantitative AI and quantum-inspired technologies to solve real-world problems across drug discovery, materials science, cybersecurity, and navigation. They build large quantitative models (LQMs) grounded in physics and chemistry to predict molecular properties, accelerate therapeutic design, and simulate complex chemical and catalytic processes, while also applying their expertise in AI and post-quantum cryptography to enhance digital security and navigation in GPS-denied environments.
Staff ML Research Scientist – Co-Folding, Affinity
🕒 March 31
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SandboxAQ
51 - 200 employees
Founded 2021
🤖 Artificial Intelligence
🔒 Cybersecurity
💊 Pharmaceuticals
Artificial Intelligence • Cybersecurity • Pharmaceuticals
SandboxAQ is a company developing quantitative AI and quantum-inspired technologies to solve real-world problems across drug discovery, materials science, cybersecurity, and navigation. They build large quantitative models (LQMs) grounded in physics and chemistry to predict molecular properties, accelerate therapeutic design, and simulate complex chemical and catalytic processes, while also applying their expertise in AI and post-quantum cryptography to enhance digital security and navigation in GPS-denied environments.
📋 Description
• Drive the research and development of next-generation deep learning models for protein-ligand co-folding and affinity prediction. • Bridge from research to commercial utility by equipping SandboxAQ’s software products with advanced predictive capabilities. • Bring novel ideas and the content of scientific papers into the ideation, training, and benchmarking of complex models, ensuring they are optimized for large-scale, real-world drug discovery applications. • Act as a technical beacon for the team, representing SandboxAQ scientifically and shaping its vision externally and internally. • Mentor junior researchers and collaborate across engineering and product teams to foster a culture of technical rigor and rapid iteration.
🎯 Requirements
• PhD in Computer Science, Computational Chemistry, or a related field, with specific focus on structure-based deep learned affinity modelling a plus. • At least 4 years of post-PhD experience, including experience in a professional industry setting, with a track record of delivering scientific impact that translates to product. • Direct, hands-on experience developing and executing leading-edge co-folding and/or affinity prediction models, from proof of concept to productionized workflows. • Proven excellence in co-folding and/or affinity prediction, as demonstrated by participation in industrial projects and/or academic publications. • Experience functioning within a professional software team, including proficiency in Python and modern ML frameworks (PyTorch/JAX) at scale.
🏖️ Benefits
• Competitive base salary, performance-based incentives or bonuses (where applicable), and equity participation. • Comprehensive medical, dental, and vision coverage for employees and dependents with generous employer premium contributions. • Retirement savings with company matching. • Paid parental leave and inclusive family-building benefits. • Flexible paid time off, company-wide seasonal breaks, and support for flexible work arrangements that enable sustainable performance. • Opportunities for continuous learning and growth through on-the-job development, cross-functional collaboration, and access to internal learning and development programs.
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