ML Research Engineer, AI for Life Sciences

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SandboxAQ

WebsiteLinkedInAll Job Openings

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

• Bring novel ideas and the content of scientific papers into high-performing and robust scientific code. • Lead the ideation, benchmarking, and execution of complex datasets and ML models, ensuring seamless integration into our large-scale simulation frameworks. • Drive software through the entire product lifecycle—from foundational research and implementation to launch and long-term support—ensuring technical excellence at every stage.

🎯 Requirements

• PhD, or research-focused MSc, in Computer Science, Physics, Chemistry, or a related quantitative field focused on advanced computational methods. • Staff (5+ years) industry experience developing productionized software in professional teams. • Experience or training in data-science related tasks related to structural biology. • Expertise translating research papers into concrete ML software artifacts. • Experience supporting models in external-facing products, demonstrating the ability to bridge the gap between "research code" and "product code". • Direct experience in biopharma or training leading-edge affinity, structure-prediction, or generative chemistry models (highly desired). • A history of developing and launching successful commercial software products within a professional engineering team (highly desired). • Familiarity with MLOps practices on major cloud platforms to support automated scaling and model monitoring (highly desired). • Experience working in interdisciplinary environments where AI intersects with physical or biological sciences (highly desired).

🏖️ 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.