Staff Machine Learning Research Scientist (Co-Folding and Affinity)
Top Benefits
About the role
- 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 Staff ML Research Scientist focusing on Co-Folding & Affinity, you will occupy a senior position architecting our ML biopharma capabilities
- Your central purpose is to redefine the state-of-the-art in structure prediction and binding affinity, transforming these breakthroughs into core components of our software suite
- Within your first year, you will: pioneer novel deep learning architectures that surpass current benchmarks, orchestrate the seamless integration of these models into production-ready drug discovery pipelines, and solidify SandboxAQ’s scientific authority through high-impact publications and industry-shaping research
- Pioneer Novel Architectures: Drive the research and development of next-generation deep learning models for protein-ligand co-folding and affinity prediction
- Architect Product Integration: Bridge from research to commercial utility by equipping SandboxAQ’s software products with advanced predictive capabilities
- Orchestrate Technical Strategy: 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
- Champion Scientific Excellence: Act as a technical beacon for the team, representing SandboxAQ scientifically and shaping its vision externally and internally
- Scale High-Performing Teams: Mentor junior researchers and collaborate across engineering and product teams to foster a culture of technical rigor and rapid iteration
Benefits
- Stock options
- Unlimated vacation (PTO) and flexible work culture
- Company-wide winter and summer breaks to unwind
- Best-in-class health plans: Medical, dental and orthodontics, and vision
- Family planning and fertility benefits
- Military leave
- 100% paid parental leave
- 401k with company matching
- Education stipends
- Financial wellness resources- World-Class Domain Expertise: PhD in Computer Science, Computational Chemistry, or a related field, with specific focus on structure-based deep learned affinity modelling a plus
- Domain-Specific Excellence: Proven excellence in co-folding and/or affinity prediction, as demonstrated by participation in industrial projects and/or academic publications
- Proven Industrial Impact: 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
- Professional Engineering Fluency: Experience functioning within a professional software team, including proficiency in Python and modern ML frameworks (PyTorch/JAX) at scale
- Frontier Technical Skills: Direct, hands-on experience developing and executing leading-edge co-folding and/or affinity prediction models, from proof of concept to productionized workflows
- Postdoctoral Experience: In deep learned structure-based affinity models
- Commercial Success: Experience shipping commercial-grade software products within the biopharma or tech sectors
- Interdisciplinary Leadership: Relevant postdoctoral experience that demonstrates an ability to lead research at the intersection of AI and physical sciences
- Technical Vision: Experience setting the technical roadmap for a specialized research group or project
- Deep Biopharma Context: Direct experience working within drug discovery pipelines, understanding the specific challenges of lead optimization and hit-to-lead phases
- Research Visibility: A track record of contributions to the scientific community, such as first-author publications in top-tier venues like NeurIPS, ICML, or CVPR
- Agentic Coding: Deep familiarity with agentic coding tools (e.g. Claude code, Codex)
Not the right fit? Search for Machine Learning Research Scientist jobs in Canada {{REMOTE}}
About SandboxAQ
In the tech and data intelligence worlds, a sandbox is where innovation is born. It’s a place where the brightest free-thinking minds from across disciplines come together to reimagine what’s possible. A collaborative environment where the whole is infinitely greater than the sum of the parts.
At SandboxAQ, this forward-looking vision is core to everything we do. It’s how we became who we are and it’s how we know our solutions can shift the way your business competes in tomorrow’s marketplace. As the world enters the third quantum revolution, AI + Quantum software will address significant business and scientific challenges. SandboxAQ is a B2B company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) deliver critical advances in life sciences, financial services, navigation, cyber and other sectors. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors including T. Rowe Price, Eric Schmidt, Breyer Capital, Guggenheim Partners, Marc Benioff, Thomas Tull, Paladin Capital Group, and others.
Similar Jobs
Staff Machine Learning Research Scientist (Co-Folding and Affinity)
Top Benefits
About the role
- 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 Staff ML Research Scientist focusing on Co-Folding & Affinity, you will occupy a senior position architecting our ML biopharma capabilities
- Your central purpose is to redefine the state-of-the-art in structure prediction and binding affinity, transforming these breakthroughs into core components of our software suite
- Within your first year, you will: pioneer novel deep learning architectures that surpass current benchmarks, orchestrate the seamless integration of these models into production-ready drug discovery pipelines, and solidify SandboxAQ’s scientific authority through high-impact publications and industry-shaping research
- Pioneer Novel Architectures: Drive the research and development of next-generation deep learning models for protein-ligand co-folding and affinity prediction
- Architect Product Integration: Bridge from research to commercial utility by equipping SandboxAQ’s software products with advanced predictive capabilities
- Orchestrate Technical Strategy: 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
- Champion Scientific Excellence: Act as a technical beacon for the team, representing SandboxAQ scientifically and shaping its vision externally and internally
- Scale High-Performing Teams: Mentor junior researchers and collaborate across engineering and product teams to foster a culture of technical rigor and rapid iteration
Benefits
- Stock options
- Unlimated vacation (PTO) and flexible work culture
- Company-wide winter and summer breaks to unwind
- Best-in-class health plans: Medical, dental and orthodontics, and vision
- Family planning and fertility benefits
- Military leave
- 100% paid parental leave
- 401k with company matching
- Education stipends
- Financial wellness resources- World-Class Domain Expertise: PhD in Computer Science, Computational Chemistry, or a related field, with specific focus on structure-based deep learned affinity modelling a plus
- Domain-Specific Excellence: Proven excellence in co-folding and/or affinity prediction, as demonstrated by participation in industrial projects and/or academic publications
- Proven Industrial Impact: 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
- Professional Engineering Fluency: Experience functioning within a professional software team, including proficiency in Python and modern ML frameworks (PyTorch/JAX) at scale
- Frontier Technical Skills: Direct, hands-on experience developing and executing leading-edge co-folding and/or affinity prediction models, from proof of concept to productionized workflows
- Postdoctoral Experience: In deep learned structure-based affinity models
- Commercial Success: Experience shipping commercial-grade software products within the biopharma or tech sectors
- Interdisciplinary Leadership: Relevant postdoctoral experience that demonstrates an ability to lead research at the intersection of AI and physical sciences
- Technical Vision: Experience setting the technical roadmap for a specialized research group or project
- Deep Biopharma Context: Direct experience working within drug discovery pipelines, understanding the specific challenges of lead optimization and hit-to-lead phases
- Research Visibility: A track record of contributions to the scientific community, such as first-author publications in top-tier venues like NeurIPS, ICML, or CVPR
- Agentic Coding: Deep familiarity with agentic coding tools (e.g. Claude code, Codex)
Not the right fit? Search for Machine Learning Research Scientist jobs in Canada {{REMOTE}}
About SandboxAQ
In the tech and data intelligence worlds, a sandbox is where innovation is born. It’s a place where the brightest free-thinking minds from across disciplines come together to reimagine what’s possible. A collaborative environment where the whole is infinitely greater than the sum of the parts.
At SandboxAQ, this forward-looking vision is core to everything we do. It’s how we became who we are and it’s how we know our solutions can shift the way your business competes in tomorrow’s marketplace. As the world enters the third quantum revolution, AI + Quantum software will address significant business and scientific challenges. SandboxAQ is a B2B company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) deliver critical advances in life sciences, financial services, navigation, cyber and other sectors. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors including T. Rowe Price, Eric Schmidt, Breyer Capital, Guggenheim Partners, Marc Benioff, Thomas Tull, Paladin Capital Group, and others.