ML Research Engineer, AI for Life Sciences

About SandboxAQ SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors. We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders. At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact. The Opportunity The AI Sim R&D team creates leading edge ML and physics-based models ("LQMs") to advance drug and materials discovery. We are a flexible, creative, and impact driven team of multidisciplinary scientists and engineers, whose products dramatically accelerate the creation of molecules and medicines. As a ML Research Engineer, you will bring cutting edge research into production-grade reality, tasked with making in silico design the dominant paradigm in drug discovery. Your central purpose is to architect, scale, and optimize the scientific codebases that power our LQMs. Over your first year, you will drive the transition of high-impact prototypes into robust products, orchestrate distributed training pipelines on world-class GPU infrastructure, and pioneer hardware-level optimizations that push the boundaries of computational chemistry. Key Responsibilities Research, Architect, and Scale: Bring novel ideas and the content of scientific papers into high-performing and robust scientific code. ML Engineering: Lead the ideation, benchmarking, and execution of complex datasets and ML models, ensuring seamless integration into our large-scale simulation frameworks. Ownership of the Lifecycle: Drive software through the entire product lifecycle—from foundational research and implementation to launch and long-term support—ensuring technical excellence at every stage. Essential Skills & Experience Academic Foundation: PhD, or research-focused MSc, in Computer Science, Physics, Chemistry, or a related quantitative field focused on advanced computational methods. Software Excellence: Staff (5+ years) industry experience developing productionized software in professional teams. Structural Biology Exposure: Experience or training in data-science related tasks related to structural biology. Research Translation: Expertise translating research papers into concrete ML software artifacts. Product Lifecycle Mastery: Experience supporting models in external-facing products, demonstrating the ability to bridge the gap between "research code" and "product code". Highly Desired Skills & Experience Domain Expertise: Direct experience in biopharma or training leading-edge affinity, structure-prediction, or generative chemistry models. Commercial Insight: A history of developing and launching successful commercial software products within a professional engineering team. Advanced MLOps: Familiarity with MLOps practices on major cloud platforms to support automated scaling and model monitoring. Collaborative Innovation: Experience working in interdisciplinary environments where AI intersects with physical or biological sciences. Why Join Us? We offer competitive compensation, a comprehensive benefits package, and opportunities for professional growth. Compensation: Competitive base salary, performance-based incentives or bonuses (where applicable), and equity participation. Benefits: 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. Work-Life Balance: Flexible paid time off, company-wide seasonal breaks, and support for flexible work arrangements that enable sustainable performance. Career Development: Opportunities for continuous learning and growth through on-the-job development, cross-functional collaboration, and access to internal learning and development programs. SandboxAQ Welcomes All We are committed to fostering a culture of belonging and respect, where diverse perspectives are actively sought and valued. Our multidisciplinary environment provides ample opportunity for continuous growth - working alongside humble, empowered, and ambitious colleagues ready to tackle epic challenges. Equal Employment Opportunity: All qualified applicants will receive consideration regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. Accommodations: We provide reasonable accommodations for individuals with disabilities in job application procedures for open roles. If you need such an accommodation, please let a member of our Recruiting team know. Read: Guidance for candidates on using AI Tools in interviews

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.

Requires a PhD or research-focused MSc in a quantitative field and at least 5 years of industry experience in production software development. Candidates must have expertise in translating research papers into ML artifacts and experience with structural biology data science.

• Medical coverage • Dental coverage • Vision coverage • Retirement savings with company matching • Paid parental leave • Family-building benefits • Flexible paid time off • Company-wide seasonal breaks • Equity participation • Performance-based incentives

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• Machine Learning Engineering
• Production Software Development
• Structural Biology
• Computational Chemistry
• MLOps
• Distributed Training Pipelines
• GPU Optimization
• Research Translation
• Product Lifecycle Management
• Generative Chemistry Models
• Structure Prediction
• Cloud Platforms
• Cross-Functional Collaboration
• Continuous Development
• Pipelines
• Mathematical Chemistry
• Research Papers
• Concept Drift Detection
• MLOps (Machine Learning Operations)
• Ideation
• Distributed Machine Learning
• Open Innovation
• Time Off Management
• Learning and Development Programs and Policies
• Quantitative Modeling
• Research
• Artificial Intelligence
• Chemistry
• Benchmarking
• Biology
• Collaborative Innovation Networks
• Computer Science
• Creativity
• Cyber Security
• Drug Discovery
• Financial Services
• Forecasting
• Life Sciences
• Machine Learning
• Mathematics
• Physics
• Data Science

• Science & Research
• Technology
• Software
• Engineering
• Healthcare
• Life Sciences Research Assistant
• Machine Learning Engineer
• Software Developers
• Computer and Information Research Scientists

Formation minimale

Maîtrise

Expérience minimale

5+ ans

Langue de l’offre

anglais

Heures de travail

40 heures par semaine

Exigences de lieu

Country, Canada